Flatfish intestinal microbiota depend on various host traits, and vary with sediment type and bottom trawling effort

24 The intestinal microbiota of fishes support digestion, nutrient uptake and play an 25 important role in the immune system, development and reproduction. Flatfish live in 26 close contact with the seafloor, and are particularly exposed to anthropogenic 27 disturbances such as bottom trawling. Bottom trawling impacts the ecosystem in 28 various ways and it recent evidence indicates that the microbial composition and 29 diversity in marine sediments varies with fishing intensity. It is presently unknown 30 whether this trawling signal applies to the seafloor alone, or may also extend to 31 microbiota of marine holobionts inhabiting it, such as flatfishes. Here, three flatfish 32 species (Buglossidium luteum , Limanda limanda and Pleuronectes platessa ) were 33 sampled across the southeastern North Sea. We characterized the intestinal 34 microbiota using 16S rDNA metabarcoding of 162 individuals, and disentangled how 35 intestinal microbial composition and diversity are jointly shaped by various host traits 36 (species, sex, age, weight, and condition factor) and environmental factors (sediment 37 type and trawling intensity). Intestinal diversity varied among species and changed 38 with age, weight and sediment type. Community composition was dependent on 39 species, age, condition factor and sediment type. In addition, we found that trawling 40 intensity explained shifts in intestinal microbial community composition, suggesting 41 that the known impacts of bottom trawling on the benthic environment may cascade 42 to intestinal microbiota of flatfish. Our findings provide important insight into host-43 microbiota interactions in marine ecosystems and highlight the interplay between 44 host traits and environment as drivers of intestinal microbial diversity and community 45 composition in flatfish. 46 47

bottom trawling, fishing impacts, intestinal microbiota, gut microbiome, 48 fish holobiont 49 50 Highlights 51 • Flatfish microbiota are shaped by host traits and environmental factors 52 • Host species and age affect intestinal microbial diversity and composition 53 • Intestinal microbiota vary along a bottom trawling intensity gradient 54 • Bottom trawling impacts may cascade from sediments to fish intestinal microbiota 55 56 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint 1. Introduction 57 Comprising a diverse and complex ecosystem of bacteria, archaea, fungi, 58 protozoa, and viruses, the intestinal microbiota play a critical role in animal 59 physiology in general, and in fish particularly (Arun & Midhun 2023; Rombout et al. 60 2011). For instance, the intestinal microbiota influence immune functions, 61 homeostasis, food digestion, growth and reproduction (Nayak 2010; Nie et al. 2017; 62 Ray et al. 2012; Rolig et al. 2017; Tarnecki et al. 2017; Wu et al. 2012). In humans, 63 where intestinal microbiota have been studied most extensively, healthy intestinal 64 microbiota have even been shown to enhance brain health and stress response 65 (Dinan & Cryan 2016). Due to their shorter generation times and higher genetic 66 variability, microbiota can respond more rapidly to environmental changes, thereby 67 influencing the adaptive responses of their marine hosts (Leray et al. 2021; Wilkins et 68 al. 2019). 69 The factors that shape the composition and diversity of these microbial 70 communities through space and time are less well understood, but appear to be 71 habitat, species and tissue specific (Ghotbi et al. 2022; Huang et al. 2020; Kanika et 72 al. 2025; Li et al. 2017), and correlate with variables such as diet, age, pollutants, 73 salinity or temperature (Adamovsky et al. 2018; Bolnick et al. 2014; Lozupone & 74 Knight 2007; Nayak 2010; Ringoe & Birkbeck 1999). 75 As the largest and most diverse group of vertebrates comprising more than 76 30,000 species (Fan et al. 2020), fish play an essential role in a variety of aquatic 77 ecosystems. Notably, they contribute to maintaining the biodiversity, stability and 78 resilience of those ecosystems. Further, as a fundamental part of aquatic food webs, 79 they ensure the recycling and transport of diverse nutrients, even between aquatic 80 and terrestrial ecosystems (Holmlund & Hammer 1999). As consumers in marine 81 food webs, fish contribute to the biological carbon pump by transporting carbon to the 82 seafloor, thereby helping to mitigate the impacts of climate change (Saba et al. 83 2021). Beyond providing fundamental ecosystem services, fish account for important 84 economic value and contribute to global nutrition (FAO 2024; Viana et al. 2023). 85 Despite the high species diversity, only a small fraction is used commercially as food 86 fish (FAO 2022). For instance, in the North Sea, home to approximately 197 fish 87 species, only a small number of species accounts for the majority of total landings 88 (Froese & Pauly 2024; ICES 2022). Demersal fish, such as flatfish, account for a 89 significant proportion of these landings, highlighting their importance in the region's 90 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint fisheries (ICES 2022; Link et al. 2002). With the rapid decline of fish populations and 91 the collapse of entire commercially exploited stocks, such as the North Sea herring 92 (Clupea harengus ) in the 1970ies, gaining a deeper understanding of population 93 dynamics and fish health is increasingly important (Dickey-Collas et al. 2010; FAO 94 2024; Zhu et al. 2021). 95 Fishing practices are known to impact the marine environment, with bottom 96 trawling being the most pervasive anthropogenic disturbance of seabed habitats 97 (ICES 2022; Kaiser et al. 2002). Shallow shelf sea regions are especially subject to 98 trawling, with the central and south-eastern North Sea being among the most heavily 99 trawled areas in the world (Amoroso et al. 2018). Besides the removal of flatfish 100 directly, trawling may also indirectly impact the remaining flatfish populations, by 101 altering the communities of seabed organisms that partially form their diet, or by 102 resuspending the upper sediment layers, stirring up fine particulate matter and 103 contaminants (Kaiser et al. 2002). Furthermore, recent evidence suggests that 104 trawling may also alter the microbiota of the sediments (Bruce et al. 2022; Bonthond 105 et al. 2023). Both diet and sediment serve as crucial microbial sources for the 106 microbial communities associated with flatfishes and other seafloor-inhabiting 107 holobionts, playing a primary role in shaping the composition and diversity of their 108 intestinal microbiota. However, whether trawling impacts on flatfish diet and sediment 109 microbiota may be indirectly affecting the microbiota of seafloor dwelling holobionts, 110 including flatfishes, remains unknown. 111 To gain better insight into the flatfish intestinal microbiota and improve our 112 understanding of wild flatfish populations, we analyzed the intestinal microbiota of 113 three flatfish species (Buglossidium luteum, Risso 1810; Limanda limanda, Linnaeus 114 1758; and Pleuronectes platessa , Linnaeus 1758) that were collected in the 115 southeastern North Sea. Using 16S rDNA metabarcoding, we characterized the 116 prokaryotic communities of 162 fish. Subsequently, we used uni- and multivariate 117 generalized linear models to test the predictive potential of different variables on the 118 structure and diversity of the intestinal microbiota, each representing individual 119 hypotheses. This included a combination of host variables (i.e., species, sex, 120 condition factor, age and weight), and environmental variables (i.e., sediment type 121 and trawling intensity). In addition, we analyzed differential abundances associated 122 with these variables, to identify microbial markers that potentially fulfil important roles 123 in the flatfish intestinal microbiota. 124 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint 125 2. Material and Methods 126 127 2.1 Sampling 128 Flatfishes were sampled during an expedition with the German Research Vessel 129 Solea from 07.05.2021 to 18.05.2021 (Cruise number: SOL791). The expedition took 130 place in the Natura 2000 area in the Southeastern North Sea (Figure 1) and was 131 carried out within the frame of a systematic survey on demersal fish and epibenthic 132 fauna in the southeastern North Sea. A 2-meter beam trawl with a 20 mm mesh size 133 outer net and 4 mm mesh size codend, and a 7-meter beam trawl with a 70 mm 134 mesh size forenet and a 20 mm mesh size codend were used.. At each station, the 135 two-meter beam trawl had a towing time of five minutes on ground, while the seven-136 meter beam trawl remained on the bottom for 15 minutes. Flatfish were caught 137 exclusively during the day and for the present study the species 138 Pleuronectes/i1platessa (European plaice), Limanda /i1limanda (Common dab) and 139 Buglossidium luteum (Solenette) were selected from the catch. When possible, one 140 male and one female were randomly selected at each station. The fish were placed in 141 plastic bags and frozen at 20/i1 °C on board. After the cruise, the fish were transferred 142 to the laboratory in cooling boxes, where they were again stored at 20 /i1 °C. In total 143 183 individuals of the species P. /i1platessa, L./i1limanda and B./i1luteum were 144 analyzed. Prior to dissection of fish individuals, the sex of the thawed fish was re-145 determined. Then, the length of the fish was measured from the head to the end of 146 the tail fin and the weight was recorded. Scissors, forceps, and scalpels were 147 cleaned and sterilized with a burner before the dissection of each fish and all 148 procedures were carried out in a sterile hood. 149 To determine the age of the fish, the otoliths were removed, cleaned and stored 150 in individually in tubes, and the age was determined at the Thünen Institute of Sea 151 Fisheries (Bremerhaven, Germany). Subsequently, the stomach, intestines, liver and 152 in females also the gonads were removed, and their weight was measured 153 individually. Intestines were then collected in separate tubes and stored at -20/i1 °C for 154 DNA extraction. 155 156 2.2 DNA extraction and library preparation 157 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint To allow optimal DNA extraction from intestinal prokaryotes, intestines were cut 158 into small fragments with sterile scissors, resulting in a homogeneous suspension. 159 From this suspension, subsamples of 100 to 125 mg were used for DNA extraction 160 with the ZYMO Quick-DNA™ Fecal/Soil MicroPrep Kit (D6012; ZYMO Research) 161 according to the manufacturer's protocol. To verify potential contamination during the 162 extraction process, DNA was also extracted from several blanks. Amplicon library 163 preparation followed the two-step PCR protocol from (Gohl et al. 2016). The 16S-V4 164 region was amplified using the primers 515F (S-*-Univ-0515-a-S-19) and 806R (S-D-165 Arch-0786-a-A-20, Klindworth et al., 2013), using the Phusion Green Hot Start II 166 High-Fidelity PCR Master Mix (ThermoFisher Scientific), and 1 /i1 µl of DNA template 167 per reaction. PCRs were also conducted on Mock communities (ZYMO-D311) and 168 negative controls. The program of the first PCR included an initial denaturation step 169 of 98/i1 °C for 3:00 min, followed by 30 cycles of 98 /i1 °C for 0:30 min, 55 /i1 °C for 0:30 170 min and 72/i1 °C for 0:30 min and a final elongation step of 72 /i1 °C for 5:00 min. PCR 171 products were run through a 1% agarose gel electrophoresis and samples without a 172 visible product underwent 5 additional PCR cycles. Then, PCR products were diluted 173 1:100 and used as templates for the second PCR, which was conducted with the 174 same reagents and the indexing primers from Gohl et al. (2016). This PCR included 175 10/i1 cycles but was otherwise identical to the PCR /i1 1. The final amplicons were then 176 normalized, purified and pooled using sequelPrep plates (ThermoFisher Scientific). 177 The sequencing, on the Illumina MiSeq platform with the MiSeq Reagent /i1 Kit/i1 v3 178 (600-cycle), was done in the German Centre for Marine Biodiversity Research 179 (DZMB; Wilhelmshaven, Germany). 180 181 2.3 Data preparation and processing 182 The raw sequencing reads were quality filtered and clustered into OTUs based 183 on the 97% similarity criterion, using the OptiClust algorithm (Westcott & Schloss 184 2017) using the software MOTHUR (v.1.48.0, Schloss et al., 2009) and classified with 185 the SILVA database (v138.1, Quast et al., 2012). Finally, samples were purged of 186 reads classified as chloroplasts, mitochondria or eukaryotes, as well as those without 187 a domain level classification, and excluded from downstream analyses if the 188 remaining total read count was below 1000. The final dataset was rarefied by 189 averaging 100 replicated count tables that were subsampled to 3500 read counts. 190 191 2.4 Statistical analysis 192 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint All analyses were performed in R (v4.4.2, see for rendered scripts 193 https://github.com/gbonthond/flatfish_microbiota). We considered a total of eight host 194 and environmental variables. The host variables included species, sex, age (in 195 years), length (in cm), total weight (in grams) and Fulton's condition factor (total 196 weight/length³, Nash et al., 2006). The weight and age were transformed with a 197 natural log and the median grain size with a log-base 2. The environmental variables 198 that were considered for the analysis were the median grain size (in µm) as a proxy 199 for habitat type and the trawling intensity in swept area ratio (SAR) per year. Median 200 grain size data was obtained from the NOAH Habitat atlas portal (NOAH 2015). As a 201 measure for the trawling intensity, we used fishing intensity of the subsurface (≥ 2 cm) 202 penetrating gears from the OSPAR data & information management system (OSPAR 203 2017). Based on spearman correlation coefficients, which revealed a strong 204 correlation between length and weight (Spearman’s rank coefficient = 0.99, Figure 205 S1, and see Figures S2-5 for more details on the host variables), it was decided to 206 use the variable weight as an indicator of size and exclude length from downstream 207 analyses. 208 To evaluate the impact of the remaining predictors on the diversity of the 209 intestinal microbial community, we calculated the OTU richness and the effective 210 number of OTUs (Jost 2006). On both responses, we fitted linear mixed models 211 (LMMs) using the R package lme4 (v1.1-35.5, Bates et al., 2015). First a global 212 model was fitted with the same structure as used for the PERMANOVA (i.e., the main 213 effects and all possible interactions with the factor species identity) and with the 214 station identity as a random effect. Model assumptions were assessed using 215 diagnostic plots. Model selection was then performed for both response variables by 216 comparing the global model to all possible simpler models, keeping the random effect 217 fixed. The best model was selected based on the corrected Akaike Information 218 Criterion (AICc). 219 The community composition of the intestinal microbiota was analyzed with 220 PERMANOVA (Anderson 2001) with the adonis2() function in the R package vegan 221 (v2.6.8 (Oksanen et al. 2013), based on Bray Curtis distances and 9999 222 permutations. To test whether predictors had general effects applicable to all species, 223 as well as species-specific effects, all seven predictors were included along with all 224 possible second order interactions with the factor species identity. To visualize 225 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint community similarity patterns, we conducted non-metric multidimensional scaling 226 (nMDS) based on Bray Curtis distances, using the R package vegan (v2.6.8). 227 Subsequently, a differential abundances analysis was conducted to identify 228 microbial markers for each of the predictors. First, the OTU dataset was reduced to 229 OTUs with at least 1% occurrence and at least 0.1% relative abundance. Second, a 230 multivariate generalized linear model (mGLM) was fitted on the reduced community 231 matrix with the package mvabund (v4.2.1, Wang et al., 2012). This model included all 232 seven predictors and assumed a negative binomial distribution. Third, the estimated 233 model coefficients were used to identify marker OTUs for each predictor, with 234 coefficients considered significant if the respective 95% confidence intervals did not 235 overlap with zero. To identify species-specific OTUs, the mGLM was fitted three 236 times, each time using a different species as the reference level, allowing us to obtain 237 pairwise estimates of species differences. The two coefficients and standard errors of 238 the differences with both other species were then pooled to obtain estimates and 239 confidence intervals for species-specific OTUs. 240 241 242 3. Results 243 After quality filtering a total of 162 samples remained. These belonged to 65 244 individuals of the species B./i1luteum, 51 of L. /i1limanda, and 46 of P. /i1platessa, and 245 included 96 females and 66 males. The rarefied community matrix counted 12,676 246 OTUs. Pseudomonadota is the most abundant phylum followed by Actinomycetota, 247 Planctomycetota, Bacillota, and Verrucomicrobiota. At the family level, Pirellulaceae, 248 Ilumatobacteraceae, Paracoccaceae, Hyphomicrobiaceae, and 249 Actinomarinales_uncultured were the five most abundant groups, accounting for 250 36.7% of the total OTU abundance (Figure 2). 251 While the intestinal microbiota were generally dominated by a combination of 252 taxa from the phyla Pseudomonadota, Planctomycetota and Actinomycetota, some 253 samples deviated from this pattern and only counted few taxa (e.g., 254 Mycoplasmataceae or Hyphomicrobiaceae), or taxa that were not among the 30 most 255 abundant families. 256 257 3.1 Diversity 258 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint From the comparison of models fitted on the effective number of OTUs (ENO) the 259 best model yielded only trawling intensity as informative predictor (Table S1). 260 However, the effect of trawling intensity on ENO was not significant ( χ ²1 = 3.06, p = 261 0.080, Table S2) and the model explained < 2% of the variation (R 2m = R2c = 0.019). 262 In contrast, for OTU richness, the best model (R2m = 0.151, R2c = 0.225) included the 263 variables species ( χ ²2 = 7.33, p = 0.026), age ( χ ²1 = 5.05, p = 0.025), weight ( χ ²1 = 264 3.89, p = 0.049), the median grain size ( χ ²1 = 7.77, p = 0.005) and the interaction 265 between the median grain size and species ( χ ²2 = 6.74, p = 0.034, (Table S1-S2). 266 Post-hoc pairwise comparisons (adjusting p-values to control for familywise error 267 rates with the Holm method) among species, revealed significant differences in OTU 268 richness between B./i1luteum and P./i1platessa (t167 = -2.525, p = 0.030) and between 269 L./i1limanda and P./i1platessa (t158 = -2.605, p = 0.030), and identified that of species-270 specific changes in OTU richness with the median grain size, only L./i1limanda was 271 significant (t116.9 = -3.209, p = 0.005, Figure 3, Table S3). 272 273 3.2 Community composition 274 NMDS (based on Bray-Curtis distances) did not reveal strong clustering patterns, 275 but indicated that community composition varied with age, condition factor, median 276 grain size and trawling intensity (Figure4A), and subtly differed among species 277 (Figure 4B). 278 These patterns were confirmed by the PERMANOVA analysis, which could 279 explain only 16.9% of the overall variation in community composition, but resolved 280 the variables species (F2,141 = 1.678, p/i1 </i1 0.001, R2 = 0.020), condition factor (F1,141 281 = 1.561, p/i1 =/i1 0.015, R 2 = 0.015), the interaction between condition factor and 282 species (F2,141 = 1.311, p/i1 =/i1 0.036, R2 = 0.036), age (F2,141 = 1.834, p = 0.003, R2 = 283 0.011), median grain size (F 1,141 = 3.621, p /i1 </i1 0.001, R 2 = 0.021) and trawling 284 intensity (F 1,141 = 3.488, p /i1 </i1 0.001, R 2 = 0.021) as significant predictors of 285 community composition. 286 287 3.3 Differential abundances 288 The differential abundance analysis (Figure 5A) identified various OTUs that 289 were negatively or positively associated with trawling intensity (negative: 29, positive: 290 24, Figure 5B), and median grain size (negative: 12, positive 35, Figure 5C). The host 291 variable with the highest amount of differentially abundant OTUs was the condition 292 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint factor (negative: 13, positive: 11, Figure 5D), followed by age (negative: 3, positive: 293 10, Figure 5E). For B. luteum (Figure 5F), L. limanda (Figure 5G), and P. platessa 294 (Figure 5H), the relative abundance of 6, 10, and 10 OTUs, respectively, increased 295 exclusively with each species. Additionally, 16 OTUs showed significantly lower 296 relative abundance in B. luteum, 12 in L. limanda, and 2 in P. platessa. 297 298 4. Discussion 299 This study provides new insights into the intestinal microbial community of three 300 flatfish species from the Southeastern North Sea, highlighting the influence of 301 environmental and host predictors on bacterial diversity and community composition. 302 Overall, the predictors evaluated in this study were able to account for a portion of 303 the total variation, but our models also indicated substantial variation to remain 304 unexplained, indicating that other variables, not examined in the present study, 305 importantly contribute as well to microbial composition and diversity in the fish 306 intestines. The significance of sediment properties (i.e., measured by the median 307 grain size) and trawling intensity emphasizes the important role of environmental 308 factors, which is consistent with previous studies (Hovda et al. 2012; Leray et al. 309 2021; MacFarlane et al. 1986; Ramírez & Romero 2017; Smith et al. 2015). 310 Additionally, we identified several host variables (species, age, condition factor and 311 weight) that contribute to diversity as well as to community composition. However, 312 while we expected that intestinal microbiota would vary between sexes our study 313 found no significant differences between females and males on either diversity or 314 community composition, suggesting that other factors, such as environmental 315 influences or host genetics, play a more dominant role in shaping the microbial 316 community. 317 It is important to emphasize that an interplay of different factors shapes the 318 intestinal microbial community (Egerton et al. 2018; Kanika et al. 2025; Xie et al. 319 2024). Some environmental variables such as temperature (Givens 2014; Neuman et 320 al. 2016), salinity (Dehler et al. 2017; Hieu et al. 2022; Lozupone & Knight 2007), 321 water microbiota (Giatsis et al. 2015; Xiong et al. 2019), pollutants (Adamovsky et al. 322 2018; Mulcahy 2002; Spilsbury et al. 2022; Suzzi et al. 2022) or diet (Bolnick et al., 323 2014; Li et al., 2017; Liu et al., 2016a; Xia et al., 2014), were not considered in this 324 study, although they are known to affect the intestinal microbiota of fish. Diet 325 especially, is known to have a primary influence on the diversity and composition of 326 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint intestinal microbiota (Bolnick et al., 2014; Li et al., 2017; Liu et al., 2016a; Xia et al., 327 2014). While variation in diet may be partially captured by both host and 328 environmental variables, we did not have direct information of dietary intake of 329 individual flatfishes, which makes other dietary factors likely candidate sources for 330 the variation that this study could not explain. 331 The presence of several similar bacterial taxa in the intestinal microbiota of one 332 or more fish species from different populations suggests that these taxa play an 333 important role in host intestinal functions (Roeselers et al. 2011). As reviewed in the 334 study by Rombout et al. (2011), the phylum Pseudomonadota is the most common in 335 the intestinal microbial community in fish, as it is in B. luteum, L. limanda, and 336 P. platessa in this study comprising about 29% of all reads. Another review by 337 Ghanbari et al. (2015) found that the phyla Pseudomonadota, Bacteroidetes, and 338 Bacillota make up to 90% of the fish intestinal microbiota. For the here studied flatfish 339 species, these phyla account for only ~40% of all amplicon reads. Instead, the phyla 340 Actinomycetota and Planctomycetota make up a significantly larger share, with the 341 most abundant three phyla accounting for around 70% of the reads found. 342 343 4.1 Intestinal microbiota vary among flatfish species 344 It is well known that the intestinal microbiota are species dependent and often 345 vary even among closely related species (Miyake et al. 2015; Navarrete et al. 2012; 346 Smith et al. 2015; Xie et al. 2024). For instance, Miyake et al. (2015) showed that 347 intestinal microbial community composition differed even among closely related 348 species within the same genus ( Acanthurus). The three species analyzed in this 349 study are more distantly related, belonging to the same order (Pleuronectiformes): 350 P. platessa and L. limanda are both members of the family Pleuronectidae, while 351 B. luteum belongs to the family Soleidae (Ahyong et al. 2023). Given that 352 evolutionary distance is positively correlated with differences in intestinal microbiota, 353 it is expected that these species have distinct intestinal microbiota (Li et al., 2017). 354 Moreover, Smith et al. (2015) examined the intestinal microbiota of different 355 populations of threespine stickleback ( Gasterosteus aculeatus ) and found that its 356 composition and diversity varied, with more genetically divergent populations having 357 more distinct intestinal microbiota. Our results are in line with this, showing that both 358 community composition and OTU-richness varied among the three flatfish species. In 359 addition, we found that changes in composition with the condition factor were 360 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint species-specific, and changes in OTU richness with sediment type were different 361 among species. 362 Our study identified 6 OTUs that were significantly more abundant in B. luteum, 363 and 10 OTUs in both P. platessa and L. limanda. Interestingly, one of the L. limanda 364 specific OTUs was classified to the genus Endozoicomonas, which is recognized as 365 a diverse symbiont, found across a wide range of marine animals, including sponges, 366 corals, mollusks, and fish (Neave et al. 2016). While the flatfish species studied here 367 are benthic predators, there are subtle dietary differences. A study by Schückel et al. 368 (2012), examined the dietary overlap among four flatfish species, including the 369 flatfish studied here, throughout the German Bight and found differences in prey 370 selection. This prey resource partitioning among species likely contributes to the 371 differences in prokaryotic community composition and diversity found here among 372 species. Beyond species-specific dietary differences, other unique traits may further 373 contribute to the distinct composition of the intestinal microbiota. Even though all 374 three species live in marine demersal habitats, only L. limanda and P. platessa 375 tolerate brackish water. Since salinity is an important factor influencing the 376 composition of the microbiota this may contribute to differences found in intestinal 377 community composition within species (Dehler et al. 2017; Hieu et al. 2022; 378 Lozupone & Knight 2007). Further, there are likely differences in migratory behavior 379 among the flatfishes studied here (Rijnsdorp et al. 1992; Marriott et al. 2016), as it 380 influences both physiological changes and environmental exposure, and may 381 therefore also contribute to differences among species (Llewellyn et al. 2016; 382 Hamilton et al. 2019; Liu et al. 2021). 383 384 4.2 Microbiota change with age in composition and become more diverse 385 Microbial community assembly of the intestine in fish can be divided into 386 colonization and persistence (Smith et al. 2015). The interplay between colonization 387 and persistence begins immediately after hatching when microbes start to colonize 388 the intestine (Blanch et al. 1997; Lauzon et al. 2010). In addition to the skin or gills, 389 the intestine acts as an entry point, allowing prokaryotes in the surrounding 390 environment and the first food to colonize it (Legrand et al. 2020). With each 391 successive food or water intake, the intestinal microbiota of the fish becomes more 392 different from the environment (Stephens et al. 2016) and diversifies further (Hansen 393 & Olafsen 1999). Accordingly, the diversity of intestinal microbiota tends to increase 394 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint with age (Li et al. 2017; Llewellyn et al. 2016; Zhang et al. 2018). However, Yan et al. 395 (2016) found that diversity decreased with age in freshwater fish species. Especially 396 in early life phases, environmental factors can have a particularly strong and long-397 lasting impact on the composition of the microbiota (Stephens et al. 2016). 398 Considering that fish are exposed to various factors throughout their life that can 399 influence their bacterial community, it is natural to expect a gradual and consistent 400 change with age. Our results are in line with many other studies, who found that 401 microbial diversity in the intestines increases with age in fishes (Ringoe & Birkbeck 402 1999; Zhang et al. 2018), as well as in humans (Nayak, 2010). In the studied flatfish 403 species, we found a similar increasing trend in OTU richness (but not on the effective 404 species number). Furthermore, community composition changed with age, and we 405 identified 6 OTUs that were significantly less abundant while 7 OTUs decreased with 406 age. 407 408 4.3 Intestinal microbiota do not differ between females and males 409 Our data showed no evidence for differences in diversity between sexes. These 410 findings are somewhat contrasting to other studies on fish intestinal microbiota where 411 more pronounced differences have been detected between females and males 412 (Chen et al. 2022; Liu et al. 2016a; Piazzon et al. 2019). In a study by Martyniuk et al. 413 (2022) a comparison between females and males in zebrafish found also no 414 differences in diversity between sexes, but several individual taxa were more 415 common in either males or females. For example, male zebrafish showed higher 416 abundance in the families Erythrobacteraceae and Lamiaceae (Martyniuk et al. 417 2022). In another study by Li et al. (2016) on largemouth bronze gudgeon (Coreius 418 guichenoti), certain taxa were found to differ in abundance between sexes. 419 Pseudomonadota was the most abundant phylum in males, whereas females 420 exhibited dominance of five different phyla. Additionally, Li et al. (2016) found 421 significant differences in diversity. Such sex-associated differences may be explained 422 by dietary variations between females and males (Bolnick et al. 2014), but could also 423 be driven by physiological factors, such as differences in hormone production (Liu et 424 al. 2016b; He et al. 2021). 425 426 4.4 Richness decreases with size and composition changes 427 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint Few studies have examined the relationship between size and the intestinal 428 microbiota in fish. Since length and weight were highly correlated, we used weight as 429 a proxy for size. Size is linked to other physiological variables such as length or age. 430 Even though a fish's weight increases with age, especially in early life stages, growth 431 rate reduces with age. This is one of the reasons that makes size and age different 432 from each other and potentially impact the intestinal microbiota differently. Our study 433 was able to disentangle these effects to some extent, as we found that OTU-richness 434 increased with age, whereas a decreasing trend in richness was found for weight, 435 after correcting for age. This result, however, is contrasting with the general 436 observation made across vertebrates (Xie et al. 2024) that larger organisms, which 437 consequently have a longer intestine, exhibiting higher intestinal microbial diversity. 438 Likewise, a study by Zhao et al. (2023) on Gymnocypris chilianensis found that 439 diversity was higher in larger individuals (>300g) than in smaller ones. These results 440 align with the island biogeography theory (MacArthur & Wilson 2001), which has 441 been linked to diversity of intestinal microbiota, predicting that as an isolated 442 ecosystem, the intestine, can support greater diversity as it increases in size (Ramos 443 Sarmiento et al. 2024). Considering the different habitats in the intestines that are 444 associated with distinct microbial communities, this correlation gets even more 445 evident (McCallum & Tropini 2023). First of all, the intestine is composed of the 446 foregut, midgut, and hindgut, each hosting distinct microbial communities (Egerton et 447 al. 2018; Hovda et al. 2007; Ktari et al. 2012; Minich et al. 2022; Ringø et al. 2006). 448 Furthermore, allochthonous microbiota are transient and associated with digesta, 449 while autochthonous microbiota colonize the mucosal surface, forming the core 450 community Interestingly, our study suggests a size-diversity relationship for flatfish 451 intestinal microbiota that is opposite from what island theory predicts. Exceptions, 452 however, exist as for instance a study on largemouth bronze gudgeon found no effect 453 of weight on diversity (Li et al. 2016). 454 455 4.5 Fulton’s condition factor is associated with compositional changes 456 In this study, we demonstrated a significant effect of the variable "condition 457 factor", as well as an interaction between species and condition factor on community 458 composition. However, no significant effect was found on diversity. Among all studied 459 host variables, condition factor was found to have most differently abundant OTUs 460 consisting of 13 negatively differently abundant OTUs and 11 positively differently 461 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint abundant OTUs. While weight provides a measure of size, the condition factor, as a 462 ratio of weight to length, offers a relative measure that reflects a fish's health and 463 food availability (Heino & Kaitala 1999). Also in this case, diet, which is known as an 464 important factor influencing the composition of the intestinal microbiota across 465 vertebrates, and specifically in fish, may be associated with the condition factor. In 466 particular, food availability, or more precisely periods of starvation, are a prime 467 example that affects the condition factor and the intestinal microbiota simultaneously. 468 Consequently, Xia et al. (2014) observed shifts in bacterial communities in Asian 469 seabass, with a significant enrichment of Bacteroidetes and a significant depletion of 470 Betaproteobacteria as a result of starvation. Although comparable studies that 471 analyze the relationship between the condition factor and the intestinal microbiota in 472 fish are rare, community composition of the human intestinal microbiota has been 473 reported to vary with the body mass index, which can be considered equivalent to 474 Fulton’s condition factor (Dominianni et al. 2015; Goodrich et al. 2014). The 475 relationship between the intestinal microbiota and the condition factor is reciprocal, 476 as some prokaryotes of the intestinal microbiota are able to break down complex 477 sugars and provide essential short-chain fatty acids and energy as well as other 478 nutrients, directly influencing the nutritional and health condition of the fish (Talwar et 479 al. 2018). Due to this fundamental importance of the microbiota for the condition of a 480 fish, the intestinal microbial diversity has been used a biomarker for fish health and 481 metabolic capacity (Xiong et al. 2019). 482 483 4.6 Microbial composition and diversity vary with sediment type 484 With their bottom-dwelling way of life and their food, which largely consists of 485 organisms living in the sediment (Schückel et al. 2012), flatfish are in close contact 486 with both the sediment and its specific microbiota. Sediment properties (i.e., median 487 grain size, mud content and organic matter content) are primary drivers of microbial 488 community composition and diversity of the top sediment layer (Bonthond et al. 489 2023). Moreover, also the organisms that make up the flatfish diet and pass through 490 their intestines vary across habitat types and are thus strongly dependent on 491 sediment properties (Huys et al. 1992; Neumann et al. 2017; Reiss et al. 2010). 492 Using the median grain size as a simple measure for sediment type (e.g., mud, sand 493 or gravel), we found that microbial diversity and composition within the flatfish 494 intestine is indeed linked with local sediment properties. 495 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint That the sediment is an important source of microbiota found in the intestine is 496 also suggested by others. Although grass carp primarily inhabit the mid to upper 497 water column, Wu et al. (2012) found that their intestinal microbiota composition 498 mainly originates from the surrounding water and sediment. Species dwelling closer 499 to the bottom sediment, such as flatfish, may be even more influenced by it. Besides 500 the highly significant association with OTU-richness and community composition, the 501 median grain size also yielded a large number of differentially abundant OTUs, with 502 47 OTUs decreasing with median grain size, and 35 OTUs increasing. 503 504 4.7 Intestinal microbial community composition varies with trawling intensity 505 We found that trawling intensity explained small but significant changes in 506 intestinal community composition. In total, we detected 24 OTUs to increase with 507 trawling intensity, while 29 OTUs decreased. While trawling activity does not impact 508 the isolated microbial ecosystems in the intestines of individual flatfishes directly, we 509 propose three potential indirect pathways that may explain this observed trend. 510 First, mobile bottom-contacting fishing gears impact the environment physically. 511 Beam trawls penetrate several centimeters deep into the seafloor, resuspending 512 large amounts of sediment and organic matter, and modifying the seabed 513 morphology (Puig et al. 2012). This affects both the water column and the seafloor, 514 with which flatfish live in close contact. 515 Second, trawling alters benthic faunal communities. In the North Sea, up to 70% 516 of benthic invertebrates, including bivalves, polychaetes, echinoderms or ophiuroids, 517 die when they get dragged by a trawl (reviewed in Eigaard et al. 2017, Sciberras et 518 al. 2018). Many of these animals naturally influence the remineralization of organic 519 matter and the regeneration of nutrients by microorganisms (Hooper et al. 2005; 520 Olsgard et al. 2008), but also make up the flatfish diet, which importantly impacts 521 intestinal microbiota composition and diversity (Ringø et al. 2006; Xie et al. 2024). 522 Link et al. (2002) analyzed dietary data of flatfish in the Northwest Atlantic over 25 523 years and found that the average weight of stomach contents of flatfish decreased in 524 heavily fished areas. This supports that trawling can influence the diet of flatfishes. 525 Moreover, besides changes in the identity of organisms in the flatfish diet, periods of 526 reduced food availability and starvation are known to alter the intestinal microbial 527 community (Xia et al. 2014). Therefore, trawling driven changes in flat fish diet may 528 impact the intestinal microbiota in different ways and present a possible cause of the 529 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint here observed association between intestinal microbial community composition and 530 trawling intensity. 531 Third, the demersal flatfish species studied here live in close contact with the 532 sediment, which also acts as a source of microbes that colonize their intestines (Wu 533 et al. 2012). Sediment microbiota have been shown to vary with bottom trawling effort 534 as well, showing a decrease in alpha diversity and change in overall community 535 composition (Bruce et al. 2022; Bonthond et al. 2023). Therefore, trawling related 536 shifts in benthic microbiota may offer another potential pathway through which 537 trawling intensity could indirectly impact the intestinal microbial community of flatfish. 538 While physical alterations to the seabed morphology, changes in faunal 539 communities and therefore diet, and shifts in sediment microbiota, present interesting 540 hypotheses for how trawling may indirectly affect flat fish intestinal microbiota, they 541 currently remain speculative. Nonetheless, they currently offer the best explanation 542 for the observed association between bottom trawling intensity and intestinal 543 microbiota composition. Moreover, they highlight the need for further investigation 544 and serve as a hypothetical basis for future research on the effects of environmental 545 disturbance caused by fishing activities on fish health and fish intestinal microbiota in 546 particular. 547 548 5 Conclusions 549 Here, we disentangled how species identity, age, size, condition factor, and 550 environmental factors (i.e., sediment type and trawling intensity), contribute to 551 shaping the intestinal microbiota of the demersal flatfish species B. luteum, 552 L. limanda and P. platessa in the southeastern North Sea. The strong effects of 553 sediment type and trawling intensity indicate that the environment plays a 554 determinant role in shaping the intestinal microbiota of these flatfishes. To the best of 555 our knowledge, this study is the first to detect an association with bottom trawling 556 intensity. This adds on previous work, that found benthic microbiota to vary along a 557 trawling gradient (Bonthond et al. 2023), and may hint that such effects could extent 558 to higher trophic levels. However, we note that substantial variation could not be 559 explained by our models, indicating that other processes, not captured by the 560 variables examined here, importantly influence fish intestinal microbiota as well. 561 Dietary factors likely account for a substantial portion of the unexplained variation in 562 both composition and diversity of the flatfish intestinal microbiota. Another important 563 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint factor that we were not able to account for is the migratory history of the flatfish 564 studied (Marriott et al. 2016; Liu et al. 2021). 565 While many studies have focused on captive fish due to their economic 566 importance in aquaculture, wild populations remain understudied (Kanika et al. 567 2025). Given that Ramírez & Romero (2017) found differences in intestinal microbial 568 communities between wild and captive Fine Flounder (Paralichthys adspersus ), and 569 Xie et al. (2024) documented such differences across vertebrates in a meta-analysis, 570 the focus of this study on wild populations contributes to narrowing this knowledge 571 gap. Furthermore, this study helps to compensate for a geographic bias, as most 572 studies on this topic to date have come from North America or East Asia, while 573 Central Europe and Africa tend to be underrepresented (Kanika et al. 2025). 574 These findings contribute to our understanding of how host variables as well as 575 environmental and anthropogenic processes may directly or indirectly affect host-576 associated microbial communities, with potential ecological and evolutionary 577 implications. As this study is the first to observe an association of trawling effort and 578 microbial community composition of flatfish intestines, it merits for more research to 579 identify the mechanisms that underly this trend, gain insight into the long-term 580 impacts, and potential consequences for fish health and population dynamics. 581 582

583 We thank the crew of the RV Solea for all their support during the fieldwork. 584 Birgit Brinkmann and Petra Schwarz are thanked for their help at the ICBM lab. We 585 are particular grateful to Valeria Adrian-Schütte and Jana Bäger (Thünen Institute of 586 Sea Fisheries) for determining the age of individual fishes through otolith analysis. 587 Further, we express our gratitude to Jessica Van der Maesen for illustrating the 588 flatfish species depicted in Figure 1. This is pu blicat ion num ber 106 th at us es dat a from 589 the Sencken berg am M ee r M e tabarcod ing an d SNG labor at or y . 590 This study was funded by the German Federal Ministry of Education and 591 research (BMBF), through DAM: MGF North Sea I and II (Grant numbers 03F0847B 592 and 03F0936C). 593 594 595 Data availability 596 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint The de-multiplexed V4-16S gene amplicon reads and associated metadata are 597 available from the European Nucleotide Archive under the Bioproject accession 598 number PRJEB88596. Data and R-scripts used for the analyses are available on 599 GitHub at https://github.com/gbonthond/flatfish_microbiota. 600 601 Author contributions 602 HH, HN, PJS and GB conceptualized the study. Field collections were 603 conducted by HH, HN and GB. MG, SK and GB conducted laboratory work. MG and 604 GB processed data and carried out the formal analysis. MG and GB drafted the 605 manuscript. All authors contributed to revising the manuscript. 606 607 Competing interests 608 The authors declare that no competing interests exist 609 610 Ethics statement 611 Animals sampled for this study were obtained from trawling catches collected 612 during regular monitoring by the Thünen Institute of Sea Fisheries aboard the 613 German Research Vessel Solea, which is operated by the Federal Office for 614 Agriculture and Food (BLE), the authority responsible for regulating fishing activities 615 in German waters. Thereby, fishing was conducted with permission from German 616 authorities. Since the animals experienced no additional stress beyond standard 617 commercial fishing practices, no further authorization or ethics approval was 618 required. The species studied are neither protected by legislation nor classified as 619 threatened or endangered. All research complied with the European directive 620 2010/63/EU on the protection of animals used for scientific purposes. 621 622 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint

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It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint Yan, Q., Li, J., Yu, Y., Wang, J., He, Z., Van Nostrand, J.D., et al. (2016). 922 Environmental filtering decreases with fish development for the assembly of 923 gut microbiota. Environ. Microbiol., 18, 4739–4754. 924 Zhang, Z., Li, D., Refaey, M.M., Xu, W., Tang, R. & Li, L. (2018). Host Age Affects the 925 Development of Southern Catfish Gut Bacterial Community Divergent From 926 That in the Food and Rearing Water. Front. Microbiol., 9, 495. 927 Zhao, Z., Zhao, H., Zhang, L., Huang, Z., Ke, H., Liu, Y., et al. (2023). Integrated 928 analysis of how gender and body weight affect the intestinal microbial diversity 929 of Gymnocypris chilianensis. Sci. Rep., 13, 8811. 930 Zhu, L., Wang, J. & Bahrndorff, S. (2021). Editorial: The Wildlife Gut Microbiome and 931 Its Implication for Conservation Biology. Front. Microbiol., 12, 697499. 932 933 934 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint Figures 935 936 Figure 1: Sampling stations in the Sylter Outer Reef area (green outline) in the 937 Southeastern North Sea and target species below. Red circles highlight the sampling 938 stations where the fish were caught. Drawings of the species studied here can be 939 seen below the map. 940 941 Figure 2: Stacked bar plot of the 30 most abundant prokaryotic families across all 942 samples, sorted by species and sex. Each color represents a family, which are sorted 943 by phylum. The length of the bars corresponds to the proportional abundance in the 944 microbiome of a fish's intestine. 945 946 Figure 3: Diversity represented as OTU richness for species, median grain size 947 (separated for species), age and weight. 948 949 Figure 4: nMDS plots based on Bray-Curtis distances display compositional 950 dissimilarities of the intestinal microbial communities. Variables that significantly 951 explain dissimilarities in community composition are shown for continuous variables 952 and displayed as vectors (A) and for species (B), with ellipses drawn around the 953 centroids based on the standard deviation of the data points. 954 955 Figure 5: (A) The number of OTUs that significantly differ in abundance, either 956 positively (grey or colored) or negatively (white) in response to environmental and 957 host predictors. Positive responses of differentially abundant OTUs are displayed 958 separately for each species in a Venn diagram, where overlapping areas indicate the 959 number of OTUs that show an increase in abundance in both species. In forest plots, 960 the differentially abundant OTUs in relation to trawling intensity (B), median grain size 961 (C), condition factor (D), age (E) and species (F-H) are illustrated. For each 962 differentially abundant OTU, a negative fold change represents a negative response 963 and a positive fold change value a positive response. The length of the bars indicates 964 the 95% confidence intervals. 965 966 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint Sampling Stations in the Sylt Outer Reef, German Bight Sampling Stations (ID) Sylt Outer Reef NATURA 2000 German border Legend Data Source: own data, NATURA Buglossidium luteum 2000 Network viewer, BKG

map: EsriTopo ESPG 3857 Overview Map Limanda limanda Pleuronectes platessa .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint P eM15_fa Solirubrobacterales_67−14 Gaiellales_uncultured Flavobacteriaceae Bacteria_unclassified Actinomycetota Bacteroidota Unclassified Mycobacteriaceae Actinomycetota_unclassified Microtrichaceae Microtrichales_uncultured Ilumatobacteraceae Actinomarinales_uncultured Thermoanaerobaculaceae Acidobacteriota Chloroflexota_KD4−96 Clostridiaceae Mycoplasmataceae Lactobacillales_unclassified Synechococcaceae Chloroflexota Bacillota Cyanobacteriota Coxiellaceae Paracoccaceae Rhizobiaceae Methyloligellaceae Hyphomicrobiaceae Desulfobulbaceae Pirellulaceae Planctomycetota Rubritaleaceae Verrucomicrobiota Chthoniobacteraceae Moraxellaceae Pseudomonadota Halieaceae Legionellaceae Vibrionaceae 0.00 0.25 0.50 0.75 female male female male female male B. luteum L. limanda P . platessa .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint species richnessrichness weight (g) grain size (µm) 0 50 100 150 200 age (years) 0 100 200 300 400 500 600 5 10 15 B. luteum L. limanda P . platessa 0 100 200 300 400 500 600 100 200 300 400 500 100 200 300 400 500 100 200 300 400 500 A B DC .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint L. limanda ♀ L. limanda ♂ P . platessa ♀ P . platessa ♂ B. luteum ♀ B. luteum ♂ A Bstress = 0.165 −6 −4 −2 0 2 4 −6 −4 −2 0 2 4 6 NMDS1 NMDS2 0.2 0.4 0.6 0.8 swept area ratio 1.0 trawling intensity grain condition factor age −1.5 −1.0 −0.5 0.0 0.5 1.0 1.5 −1.0 −0.5 0.0 0.5 1.0 NMDS1 NMDS2 −1.5 1.5 .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint 0 5 10 15 20 Otu00163 Pirellulaceae Otu00087 Oceanirhabdus Otu00192 Chlamydiales Otu00116 T epidibacter Otu00124 Rhizobiales Otu00039 Micromonospora Otu00151 Blastopirellula Otu00102 Meiothermus Otu00016 Lactobacillales Otu00158 Thermicanus Otu00091 Thiogranum Otu00095 Sandaracinaceae Otu00062 Lutimonas Otu00167 Sva0996_marine_group Otu00112 Corynebacterium Otu00074 Candidatus_Arthromitus Otu00004 Pirellulaceae Otu00082 Mycobacterium Otu00009 Rickettsiella Otu00060 Staphylococcus Otu00125 Psychrobacter Otu00054 Shewanella Otu00123 Geobacillus Otu00153 P edobacter Otu00084 Endozoicomonas Otu00016 Lactobacillales Fold change P . platessa L. limanda B. luteum Otu00015 Filomicrobium Otu00020 67−14 Otu00024 KD4−96 Otu00021 Filomicrobium Otu00005 Methyloceanibacter Otu00004 Pirellulaceae Otu00022 Actinomarinales Otu00003 Tateyamaria Otu00012 Chthoniobacteraceae Otu00009 Rickettsiella T rawling intensity 0 5 10 15 B Fold change −40 −20 0 20 D Fold change Condition factor Otu00054 Shewanella Otu00070 Rickettsiella Otu00026 Legionellaceae Otu00036 Gaiellales Otu00008 P eM15 Otu00067 Cloacibacterium Otu00023 Mycoplasmataceae Otu00045 Massilia Otu00074 Candidatus_Arthromitus L. limanda P . platessa B. luteum Trawling intensity Grain size Condition factor Age 10 1012 11 3 16 12 35 29 24 13 10 6 2 10 10 6 12 2 16 positive responsesnegative responses A H F G Otu00083 Ornithinimicrobium E Fold change Age Otu00142 Legionella Otu00015 Filomicrobium Otu00016 Lactobacillales Otu00151 Blastopirellula Otu00102 Meiothermus Otu00054 Shewanella Otu00039 Micromonospora Otu00103 Subgroup_17 Otu00132 Pir4_lineage Otu00042 Catellicoccus −10 0 10 Fold change Grain size Otu00012 Chthoniobacteraceae Otu00009 Rickettsiella Otu00018 Actinomarinales Otu00020 67−14 Otu00010 Blastopirellula Otu00017 Rubripirellula Otu00005 Methyloceanibacter Otu00003 Tateyamaria Otu00026 Legionellaceae Otu00016 Lactobacillales −7.5 −5.0 −2.5 0.0 C .CC-BY 4.0 International licenseavailable under a was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint (whichthis version posted June 2, 2025. ; https://doi.org/10.1101/2025.05.30.657041doi: bioRxiv preprint