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The loggerhead sea turtle ( Caretta caretta ), a globally distributed species, currently has a thriving population in the Mediterranean Sea, thanks to robust conservation efforts. In our study we aimed to further understand their biology in relation to their associated microorganisms. We investigated epi- and endozoic bacterial and endozoic fungal communities of cloaca, oral mucosa, carapace biofilm samples obtained from 18 juvenile, subadult and adult turtles as well as 8 respective enclosures, during a period of 3 years, by amplicon sequencing of 16S rRNA gene and ITS2 region of nuclear ribosomal gene. Our results reveal a trend of decreasing diversity of distal gut bacterial communities with the age of turtles. Notably, Tenacibaculum species show higher relative abundance in juveniles than in adults. Differential abundances of taxa identified as Tenacibaculum , Moraxellaceae , Cardiobacteriaceae , and Campylobacter were observed in both cloacal and oral samples in addition to having distinct microbial compositions with Halioglobus taxa present only in oral samples. Fungal communities in loggerheads' cloaca were diverse and varied significantly among individuals, differing from those of tank water. Our findings expand the known microbial diversity repertoire of loggerheads, highlighting interesting taxa specific to individual body sites. This study provides a comprehensive view of the loggerhead sea turtle bacterial microbiota and marks the first report of distal gut fungal communities that contributes to establishing a baseline understanding of loggerhead sea turtle holobiont. Caretta caretta wild microbiome reptile microbiota conservation efforts mycobiota Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Microbial communities associated with animal hosts play crucial roles in various aspects of the host’s development, physiology, immune response, metabolism, and reproduction, and may have an impact on the host’s evolutionary potential [ 1 , 2 ]. While the importance of sea turtle epibiosis with macro-epibionts (> 1 mm) such as barnacles has long been recognized [ 3 ], research on the microbial epibionts and endobionts of sea turtles has only recently gained attention [ 4 – 6 ]. Sea turtles hold a unique ecological role as keystone species, connecting terrestrial and coastal habitats, but they are also highly vulnerable to anthropogenic threats, such as climate change, disruption of feeding and breeding habitats, egg poaching, and accidental bycatch [ 7 – 9 ]. To lessen some of the pressure sea turtles face today, global conservation efforts have focused on safeguarding female turtles and nesting areas, and rehabilitating injured turtles [ 8 ]. Motivated by the aim of enhancing the rehabilitation and conservation of wild animals and their associated microbiomes, the studies of sea turtle gut, skin, egg, and nest microbiomes have become a forefront in sea turtle conservation research, building upon cultivation-based and pathogen-oriented research in the veterinary domain [ 10 – 12 ]. Loggerhead sea turtles ( Caretta caretta ) are a widely distributed species and are classified as vulnerable by the IUCN Red List of threatened species [ 13 ]. However, the Mediterranean subpopulation of loggerheads is considered to be of least concern due to successful conservation efforts [ 8 , 13 ]. Currently, loggerhead sea turtles’ microbiota is the second most studied, preceded only by green turtles ( Chelonia mydas ) [ 6 ]. Previous studies that used culture-dependent approaches have identified most common pathogens associated with mucosal surfaces, skin lesions (such as bacterial families Aeromonadaceae , Pseudomonadaceae , Enterobacteriaceae ), and hatchling failure ( Fusarium spp.), with the presence of antibiotic resistance genes indicating loggerheads as sentinels of antibiotic pollution in the Mediterranean [ 11 , 14 – 22 ]. Recent investigations using next-generation sequencing approaches to study the loggerhead microbiota shed light on the bacterial community structure and composition of the gastrointestinal tract [ 5 , 23 , 24 ], the impact of rehabilitation on mucosal bacteriomes [ 24 , 25 ], the effects of plastic pollution on the gut bacteria [ 26 ], variations in microbial communities driven by localities [ 27 , 28 ] or turtle anatomy [ 28 , 29 ], and host-microbial coevolution patterns [ 30 ]. On the other hand, the fungal communities associated with marine reptiles, including sea turtles, have received limited attention using cultivation-independent approaches, despite the vulnerability of sea turtles to infections caused by Fusarium spp. during early development [ 18 ]. Recent work by Guo et al. [ 31 ] provided initial insights into the fungal communities found on carapace (healthy and ulcerated), in faeces, and in the seawater of green turtle juveniles undergoing rehabilitation, however, comprehensive surveys of endobiotic fungal communities in loggerhead sea turtles have not yet been conducted. Given the ecological significance of loggerhead sea turtles in the Mediterranean basin ecosystem, their role as sentinels for pollution, and their potential to act as vectors for zoonotic diseases, a comprehensive approach including eukaryotic microorganisms is necessary to understand the loggerhead sea turtle microbiota. This knowledge will contribute to the advancement of current conservation practices and future microbial stewardship efforts [ 32 ]. The objective of this study was to investigate the bacterial and fungal communities associated with loggerhead sea turtles found in the Adriatic Sea. We analysed the bacterial communities in the cloacal, oral, and enclosure samples as well as fungal communities of cloacal and enclosure tank water samples using amplicon sequencing targeting the V3-V4 (V34) region of 16S rRNA gene and the ITS2 region of nuclear ribosomal genes, respectively. Furthermore, when available, we analysed the bacterial communities of carapace biofilm samples corresponding to turtles in this study out of which some were previously analysed as a part of our earlier study on sea-turtle epibiosis [ 28 ]. By combining these datasets, we provide a comprehensive overview of the environmental, surface, and internal microbiota of the loggerhead turtles, establishing a baseline for future holobiont approaches to studying the loggerhead sea turtles. Methods Loggerhead sea turtle sampling Loggerhead sea turtles investigated in this study were found at various locations along the Adriatic Sea coast from 2019 to 2021 (Fig. 1 a) and transported to two locations where the sampling was conducted; at Sea Turtle Clinic (STC) of the Department of Veterinary Medicine of University of Bari “Aldo Moro” in Italy and the Sea Turtle Rescue Center Aquarium Pula in Croatia. The turtles were sampled immediately upon their arrival to the rehabilitation centres or during/after rehabilitation, and prior to release (Table S1 ). Turtles were classified as juveniles, subadult and adults according to [ 33 ] and sex determination was based on observable physical characteristics when possible (Table 1 , Fig. 1 b). Additional information about sampling procedures and the loggerhead population surveyed in this study can be found in Supplementary Methods and Table S2 . The endozoic samples were collected from cloacal and oral cavities in triplicates by sterile synthetic swabs (Aptaca Nuova) as described in Filek et al. [ 25 ]. When available, enclosure tank water was collected in sterile containers, vacuum filtered on 0.2 µm sterile Whatmann polycarbonate membrane filters (Sigma-Aldrich) and stored in 2 ml tubes in 96% EtOH. All samples were stored at -20 C until DNA extraction and further processing. Additionally, corresponding epizoic carapace biofilm samples were obtained by randomly brushing the entire carapace using a toothbrush (Dentalux Classic, hard, Lidl) according to [ 28 , 34 ] and the collected material was resuspended in 96% EtOH, and stored at -20 C (Table 1 ). Each endozoic sequencing sample ID that is referred to in this manuscript has a 16S or ITS prefix, sampling event number, and suffix corresponding to sampling site: C - cloaca, O - oral cavity, W - tank water; for example, sample ID ITS0084C represents cloacal sample of fungal ITS2 sequences for sampling event 0084 (turtle ID010; Table 1 ). Epizoic samples have a TB prefix and numbering unrelated to sampling event. Table 1 Information about loggerhead sea turtles and their corresponding endozoic (16S rRNA gene and fungal ITS2 region) and epizoic (16S rRNA gene) samples (V4 – Kanjer et al. [ 28 ], V34 – this study). The turtles were retrieved at various locations in the Adriatic Sea and were admitted to Sea Turtle Rescue Center Aquarium Pula (Croatia) unless indicated otherwise ( T Tyrrhenian Sea; STC The Sea Turtle Clinic at University of Bari, Italy). The abbreviations are as follows: Clo – cloaca, Orl – oral cavity, TW – tank water, Car – carapace, NA – not available, ND – not determined. Turtle ID Turtle name Sampling event Endozoic 16S/ITS2 sample presence (+) or absence (-) * Epizoic 16S sample ID (region) Sex Age range Clo Orl TW Car ID010 Merry Fisher 0084 +/+ -/- +/+ TB139 (V4) Female Subadult ID047 Žal 0064 +/+ +/- +/+ TB115 (V4) ND Juvenile ID056 Samba 0073 +/+ +/- +/+ TB117 (V4) Female Adult ID057 Angelo STC 0074 +/+ +/- -/- NA Male Adult 0092 +/+ +/- -/- TB119 (V4) ID068 Kanooh STC 0087 +/+ +/- -/- TB145 (V4) ND Juvenile ID069 Kanfus STC 0088 +/+ +/- -/- NA ND Juvenile ID070 Futon STC 0089 +/+ +/- -/- TB149 (V4) ND Juvenile ID071 Cosmyn STC 0090 +/+ +/- -/- TB151 (V4) ND Subadult ID073 Marvin 0093 +/+ +/- +/+ TB155 (V4) ND Juvenile ID074 Ryan 0094 +/+ +/- -/- TB157 (V4) ND Juvenile ID093 Ella Ravka 0113 +/+ +/- -/- TB159 (V34) ND Subadult 0119 +/+ +/- +/+ NA ID096 Maro 0117 +/+ +/- +/+ TB167 (V34) Female Subadult 0118 +/+ +/- +/+ NA ID097 Freewings 0120 +/+ +/- +/+ NA ND Juvenile ID098 Maksimus 0123 +/+ +/- +/+ TB175 (V34) ** ND Juvenile ID117 Karlo Albano 0141 +/+ +/- -/- TB215 (V34) Male Adult ID118 Oliver Raul 0142 +/+ +/- -/- TB217 (V34) ND Juvenile ID119 Martin 0143 +/+ +/- -/- TB219 (V34) ND Juvenile ID122 Luka Amadeo 0146 +/- +/- -/- NA Male Adult * Each sample ID has a 16S or ITS prefix, sampling event number, and suffix corresponding to sampling site: C - cloaca, O - oral cavity, W - tank water; for example, sample ID ITS0084C represents cloacal sample of fungal ITS2 sequences for sampling event 0084. ** Carapace sample was collected at a different sampling event (a month prior to endozoic sampling). DNA extraction and sequencing Total DNA from swabs and filters was extracted using the DNeasy PowerSoil kit (Qiagen) following the manufacturer’s instructions with several modifications: (1) the samples were incubated in C1 solution at 65 C for one hour, (2) instead of bead beating PowerBead Tubes were vortexed horizontally for 10 min at maximum speed, and (3) all downstream incubation times at 2–8°C were increased to 15 min. The methods used for epizoic carapace biofilm samples that were sequenced for V4 region (ID010 – ID074) are described by Kanjer et al. [ 28 ]. The DNA from biofilm scrapings (ID093 – ID122) analysed only in this study was extracted via DNeasy PowerLyzer PowerSoil extraction kit (Qiagen) following the manufacturer’s instructions and modified as follows: 1) after addition of C1 solution the samples were incubated at 70°C for 10 minutes; 2) bead beating was performed at 30 Hz for 1 minute in TissueLyzer Retsch Qiagen; 3) 50 µl of C6 solution was used for DNA elution and incubated for 5 minutes at room temperature prior to centrifugation. Nuclease-free water (W4502 Sigma-Aldrich) was used as the negative control for the DNA extraction step and was processed using the DNA extraction kit in parallel to all the samples. The quality and quantity of extracted DNA was evaluated by BioSpec-nano (Shimadzu). The extracted DNA from both endozoic and epizoic samples was stored at -20 C and sent for Illumina MiSeq v3 300x2 bp paired-end sequencing to Microsynth, Switzerland. Primers used for sequencing the V34 region of 16S rRNA gene were 341F and 805R [ 35 ], and primers for fungal ITS2 region of the nuclear ribosomal gene were ITS3 and ITS4 [ 36 ]. Bioinformatics and statistics The obtained sequences had non-biological sequences trimmed by the sequencing facility and checked for quality with FastQC [ 37 ]. Sequencing data is available at EMBL ENA at accessions PRJEB62752, and PRJEB68216 for 16S rRNA gene, PRJEB62762 for ITS2 region sequences and from Kanjer et al. [ 28 ] PRJEB51458. The sequences were imported and analysed in QIIME 2 (versions 2021.8 and 2023.2) [ 38 ]. Statistical analyses were performed within QIIME 2 environment and with R. Alpha diversity indices, including Shannon’s entropy, Pielou’s evenness, Faith’s phylogenetic diversity, and observed ASVs, were calculated via q2-diversity plugin. The Kruskal-Wallis rank sum test was employed to determine differences between selected groups, followed by post-hoc pairwise comparisons using Wilcoxon rank sum exact test. For beta diversity analyses, rarefied data (sequencing depth determined by alpha rarefaction curves) were explored using the q2-diversity plugin with Bray-Curtis, Jaccard, unweighted UniFrac, weighted UniFrac distances [ 39 ]. Compositional data analysis on non-rarefied datasets was performed by calculating robust Aitchison distances using the q2-deicode plugin or the R package vegan v.2.6-4 [ 40 – 42 ]. Principal coordinates analysis (PCoA) was conducted on Bray-Curtis, Jaccard, and all UniFrac distances, while principal components analysis was performed for robust Aitchison (rPCA) using q2-diversity and q2-deicode, respectively. To assess the relative impact of factors (age range, sex, and duration of rehabilitation) on microbial communities, a multi-way permutational multivariate analysis of variance (Adonis2 PERMANOVA) with 9999 permutations was employed (Anderson, 2001) in R by using vegan v.2.6-4 and pairwiseAdonis v.0.4.1 packages [ 43 ]. Resulting p-values from all pairwise tests were adjusted using the Benjamini-Hochberg false-discovery rate (FDR) correction for multiple comparisons (reported as q-values). Differential abundance analysis was used to identify differentially abundant (DA) features in sample site pairs by using the ANCOMBC package “ancombc2” function in R [ 44 , 45 ]. Default parameters were used and pairwise testing was enabled (with Holm’s method for adjusting p-values, reported as q-values), except for DA testing in V4-trimmed sequences where the “struc_zero” was set to “TRUE” to exclude structural zeros based on sampling sites. Log fold change (LFC) indicates the scale of differential abundance between differentially abundant features. Features with p-value < 0.05 were reported as differentially abundant, and q-value < 0.05 as significantly differentially abundant. Data exploration and visualizations were conducted by using R v.4.3.0 in RStudio (R Core Team 2023) with packages listed above and in Supplement and qiime2R v.0.99.6 [ 46 ], tidyverse v2.0.0 [ 47 ], ggplot2 v3.4.2 [ 48 ], Microsoft Excel, and Adobe Illustrator. Additional details of sample processing and data analyses are available in the Supplementary Methods. Results Endozoic and tank water bacterial communities Altogether, 50 endozoic and water samples (plus one negative control) were sequenced, and 7,110,067 high quality sequences were obtained (median frequency per sample was 107,522, min. 2, max. 911,443). Denoising yielded a total of 11,105 ASVs. After filtering mitochondrial and chloroplast sequences, the number of ASVs decreased to 10,946. Forty-three samples yielded enough high-quality reads (at minimum sequencing depth above 10,000) for downstream analyses (19/21 cloacal, 16/20 oral, and 8/9 tank water samples). The highest number of observed features (OF) and phylogenetic diversity (Faith’s PD) was found in tank water samples (median OF = 603, IQR = 450; median Faith’s PD = 42.8, IQR = 53.9), followed by oral samples (median OF 473, IQR = 428; median Faith’s PD 40.2, IQR = 26.2), and cloacal samples (median OF = 308, IQR = 235; median Faith’s PD = 28.4, IQR = 20) (Fig. 2 a). ASV richness and evenness (Shannon’s index) was highest in oral samples (median = 6.28, IQR = 1.33), followed by cloacal (median = 5.62, IQR = 1.66), and tank water samples (median = 5.44, IQR = 1.67) (Fig. 2 b). Alpha diversity showed significant differences among sample sites (Kruskal-Wallis rank sum test) for OF and Faith’s PD (p-value < 0.01), while pairwise sample site comparisons (Wilcoxon rank sum test) showed differences between cloaca vs. oral samples and cloaca vs. tank water (q-value < 0.05). Shannon’s index showed weak statistical difference among samples sites (p-value = 0.04). Pearson correlation on alpha diversity indices against size of the turtle (CCL) in individual sample site groups showed strong negative correlation between cloacal samples and OF and Faith’s PD (R = -0.67, p-value = 0.002 and R = -0.59, p-value = 0.007, respectively) (Fig. 2 c), while Shannon’s index showed weaker negative correlation with CCL (R = -0.53, p-value = 0.021). Oral and tank water alpha diversity did not show any correlation effects. Further, within cloacal samples, differences were detected (Kruskal-Wallis p-value < 0.05) in age range (OF, pairwise Wilcox: adult vs. juvenile q-value = 0.024; Faith’s PD, pairwise: adult vs. juvenile q-value = 0.024) and sex of the turtles (OF, pairwise Wilcox: male vs. ND q-value = 0.004; Faith’s PD, pairwise: male vs. ND q-value = 0.018), which are directly related to turtles’ size. Bacterial communities among samples sites differed based on PERMANOVA for Bray-Curtis (R 2 = 0.09, Pr(> F) = 0.001), Jaccard (R 2 = 0.08, Pr(> F) = 0.001), unweighted and weighted UniFrac (R 2 = 0.12, Pr(> F) = 0.001; R 2 = 0.13, Pr(> F) = 0.001, respectively), and robust Aitchison distances (R 2 = 0.24, Pr(> F) = 0.002). Pairwise PERMANOVA detected differences between all sample site pairs for most beta diversity metrics except robust Aitchison where only cloaca vs. tank water and tank water vs. oral samples pairs were significantly different (Pr(> F) ≤ 0.002). Highly ranked ASVs impacting the distribution of samples on rPCA biplot were assigned to Gammaproteobacteria, order Oceanospirillales, Shewanella algae , Vibrio sp., and NS3a marine group (Fig. 2 d). Within cloacal samples, significant differences in bacterial communities were detected between adults vs. juveniles (Bray-Curtis, Jaccard, and unweighted UniFrac Pr(> F) F) F) F) F) F) = 0.018), Jaccard (R 2 = 0.14, Pr(> F) = 0.008) and unweighted UniFrac distance (R 2 = 0.16, Pr(> F) = 0.013). Pairwise PERMANOVA showed significant differences only between adults and juveniles for all above-mentioned diversity measures (Pr(> F) ≤ 0.009). The differences between adults and juveniles are observed in community composition and structure as well: phylum Verrucomicrobiota appears more often in juveniles, juveniles also have higher RA of Rhodobacterales (Alphaproteobacteria), Cardiobacterales (Gammaproteobacteria), Kineosporiales (Actinobacteriota), Oligoflexales (Bdellovibrionota), Arcobacteraceae (Campylobacterales), and more Flavobacteriales (Bacteroidota) than adults. On the other hand, adults carry more Bacteroidales (Bacteroidota), Pasteurellales (Gammaproteobacteria), Helicobacteraceae and Campylobacteraceae (Campylobacterales), and Leptotrichiaceae (Fusobacteriales). The low number of samples (≤ 10) in each age group prevented us from further differential abundance analyses. Detailed taxonomic composition of bacterial communities found in oral, cloacal and tank water samples is reported in Supplementary Results, Table S3 with additional visualizations available at Github. Differential abundance analysis detected 33 significantly DA features (post adjusting for multiple testing) out of which two were differentially abundant in cloaca (ASV467 Rhodobacteraceae and ASV4007 Shewanella algae ), and three in oral samples (ASV9794 Truepera sp., ASV6166 and ASV467 both belonging to Rhodobacteraceae ) (Fig. 3 a). Tank water had 28 DA ASVs when tested against cloaca or oral samples, most of which belonged to typical marine taxa ( Cryomorphaceae , NS3a marine group, SAR406 clade, Rhodobacteraceae , Nitrincolaceae , etc.). When collapsed to species level, 75 significantly DA taxa were detected, out of which 13 in cloaca and 15 in oral samples (Fig. 3 b). Depending on the tested sample site pair several features would be DA in both oral and cloacal samples when compared to tank water e.g., genera Marinifilum, Tenacibaculum , and Labrenzia , members of Cardiobacteriaceae and Comamonadaceae families (Fig. 3 b). Endozoic and tank water fungal communities Overall, 29 samples (plus one negative control) were sequenced, and 2,208,729 high quality sequences were obtained (median frequency per sample was 69,203, min. 11,722, max. 150,142). Denoising yielded a total of 9,547 ASVs. Based on alpha rarefaction curves, 27 samples yielded enough high-quality reads (at minimum sequencing depth at 25,000 reads) for downstream statistical analyses requiring rarefied data (19/20 cloacal, and 8/9 tank water samples). All samples except negative control were used in compositional data analyses. Tank water samples had significantly higher number of observed features and phylogenetic diversity (median = 674, IQR = 97.8; Faith’s PD median = 98.0, IQR = 10.5) than cloacal samples (median = 509, IQR = 372, Faith’s PD median = 66.6, IQR = 51.7) (Fig. 4 a) based on Kruskal-Wallis rank sum test (OF p-value = 0.008; Faith’s PD p-value = 0.007). Shannon’s diversity was not detected as significantly different between sample sites (tank water median = 8.66, IQR = 1.31; cloaca median = 6.76, IQR = 2.58) (Fig. 4 b). There were no significant differences in alpha diversity values within cloacal or tank water fungal communities when tested for age range, sex, or rehabilitation duration. The only beta diversity metric that showed significant differences between tank water and cloaca was unweighted UniFrac (R 2 = 0.06, Pr(> F) = 0.042). Unweighted UniFrac PCoA showed unclear sample groupings, however, there is a separation of cloacal and corresponding tank water samples on PCA1 axis (Fig. S1 a, corresponding samples connected with dashed lines). Compositional data analysis rPCA did not show clear separation of samples sites, and top ranked ASVs belonged to Preussia flanaganii , genus Tetracladium , order Xylariales , genus Rhizoctonia , and family Nectriaceae (Fig. S1 b). When collapsed to species level, cloacal and tank water samples each had five differentially abundant fungal taxa detected. In cloacal samples DA taxa were Leptodiscella , Elaphomyces , Sclerocleista , Gliomastix , Thelephora ; and in tank water they were Cladosporium , unidentified Leotiomycetes, unidentified Sordariomycetes (Chaetosphaerilaes), Nectria , and Humicola - although none of them were statistically significant after correction for multiple testing (Fig. 4 c). Cloacal and tank water fungal communities were represented mostly by phyla Ascomycota (average RA ± standard deviation in cloaca and tank water = 57 ± 15% and 53 ± 9%, respectively), Basidiomycota (19 ± 9% and 22 ± 3%), Glomeromycota (7 ± 6% and 10 ± 12%), Mortierellomycota (2 ± 2% and 3 ± 2%) unidentified Fungi (13 ± 20% and 11 ± 7%) (Fig. 4 d). Detailed taxonomic composition of fungal communities found in cloacal and tank water samples is reported in Supplementary Results and Table S4 . Epizoic and endozoic bacterial communities After trimming epizoic, endozoic, and tank water sequences to V4 region of 16S rRNA gene (65 samples in total) and denoising, 10,072,866 high quality sequences were merged across all sequencing events (median frequency per sample was 126,629, min. 0, max. 946,183) and yielded 13,263 ASVs. Due to reduced resolution after trimming the longer V34 region to shorter V4 region, the number of ASVs for cloacal, oral and tank water samples was expectedly lower (7,725 in V4 vs. 11,105 in V34 sequences). Carapace samples had the highest median species richness and diversity (OF median 732, IQR = 420, Faith’s PD median = 45.7, IQR = 25.2; median Shannon’s index = 5.94, IQR = 2.22), which was followed by tank water, oral and cloacal samples (Fig. 5 a, 5 b). The differences between sample sites’ alpha diversity were detected as statistically significant (Kruskal-Wallis rank sum test), however pairwise comparisons showed differences only in Faith’s phylogenetic diversity and OF: between cloaca and all other sample sites (except tank water based on OF), oral cavity and carapace. All beta diversity metrics showed significant differences between body sites for Bray-Curtis (R 2 = 0.13, Pr(> F) = 0.001), Jaccard (R2 = 0.10, Pr(> F) = 0.001), unweighted and weighted UniFrac (R 2 = 0.16, Pr(> F) = 0.001; R 2 = 0.18, Pr(> F) = 0.001, respectively), and robust Aitchison distances (R 2 = 0.09, Pr(> F) = 0.001). Pairwise PERMANOVA detected differences between all sample site pairs (Pr(> F) < 0.01). Highly ranked ASVs impacting the distribution of samples on rPCA biplot belonged to Pseudoalteromonas sp., Vibrio sp., Shewanella sp., uncultured Saccharospirillaceae , uncultured Marinifilum and uncultured Cardiobacteriaceae (Fig. 5 c). The taxonomic composition of endozoic samples and tank water using the V4 sequences resembled the one detected with V34 and it is reported in Table S5 . Additional information on taxonomic composition of epizoic bacterial communities in carapace samples is reported in Supplementary Results. Differential abundance analysis on ASVs (structural zeros excluded) detected 17 significantly DA ASVs across all sample sites (Fig. 6 ). A member of Rhodobacteraceae family (v4ASV8861) and Halioglobus sp. (v4ASV11062) were consistently DA in oral samples while the same goes for Cardiobacterium sp. (v4ASV10814) and a member of Enterobacteriaceae family (v4ASV11383) in cloaca. In carapace samples a member of Flavobacteriaceae family (v4ASV2446), cyanobacteria Leptolyngbya sp. (v4ASV4472), Ahrensia sp. (v4ASV8480), Sphingomonadaceae (v4ASV9910), Erythrobacter sp. (v4ASV9994), Gammaproteobacteria (v4ASV10111), Alteromonas sp. (v4ASV10327), Arenicella sp. (v4ASV10634), Psychrobacter sp. (v4ASV12017) and Vibrio sp. (v4ASV12307) were DA relative to other sample sites, while Marinomonas sp. (v4ASV11704) was DA abundant in carapace tested against endozoic samples, but not tank water. In tank water a member of Flavobacteriaceae (v4ASV2446) and NS3a marine group (v4ASV2817) were consistently DA (Fig. 6 ). Differential abundance analysis on taxa collapsed to species level is reported in Supplementary Results and Fig. S2 . Discussion This study provides an overview of the bacterial and fungal communities inhabiting oral and cloacal environments of loggerhead sea turtles. Additionally, we aimed to investigate bacterial communities in carapace samples in relation to the gastrointestinal tract and tank water to explore possible connections between two habitats. The carapace exhibited the highest bacterial diversity, followed by oral samples, influenced by the tank water environment, and then cloacal samples. Each sampling site had distinct microbial communities and cloacal bacterial diversity negatively correlated with turtle size and age. Conversely, fungal communities in the cloaca were distinct from tank water and showed high heterogeneity among individual turtles, with no discernible patterns related to age or sex. Cloacal bacterial diversity and structure changes with the turtle age Similarly to previous studies on cloacal microbiota in Adriatic loggerhead sea turtles, we observed changes in bacterial richness, diversity, and structure, negatively correlating with loggerheads' CCL and, consequently, their age [ 24 ]. According to research on vertebrate gut microbiomes, it is expected that the bacterial diversity increases with body size in animals with complex digestive systems, like ruminants, and decreases in animals with simple guts, often omnivores or carnivores [ 49 ]. Loggerhead sea turtles are omnivores and exhibit an ontogenetic shift from oceanic-pelagic habitats as juveniles to neritic-benthic feeding grounds as adults. However, in the Mediterranean Sea they employ an "amphi-habitat strategy", where juveniles, subadults and adults share feeding grounds and similar feeding behaviours [ 50 , 51 ]. Differences in diet, jaw size, bite force, and diving ability between juveniles and adults may result in distinct diets and digestive physiologies, potentially reflected in cloacal bacterial communities as increased richness. Studies on loggerhead diet show no significant differences in stomach contents among adults, subadults, and juveniles, but it's worth noting that softer prey like tunicates or jellyfish may not be as detectable due to easier digestion and lack of hard remains in morphology-based studies [ 50 ]. In this study, juveniles exhibited higher abundance and more frequent presence of Flavobacteriaceae and Tenacibaculum spp. in oral and cloacal samples than subadult and adult turtles. Tenacibaculum spp. are marine pathogens possibly carried by cnidarians and ctenophores as vectors [ 52 , 53 ], suggesting a higher proportion of soft prey in juveniles' diet. This study was conducted during non-winter months when jellyfish populations increase due to higher water temperatures potentially influencing prey availability. Adults likely have access to these prey types but also consume more challenging prey inaccessible to juveniles. Notably, in other studies Tenacibaculum spp. were highly abundant on loggerhead skin as well [ 28 ], indicating their propensity to inhabit marine vertebrate surfaces and gastrointestinal tracts, irrespective of animal’s diet. While in previous research the Mogibacteraceae family detected in faeces correlated with CCL [ 24 ], we did not detect it in our data, possibly due to different taxonomy databases being utilized (Greengenes vs. SILVA in our study). BLAST analysis showed ASVs assigned as Peptostreptococcales-Tissieralles closely related to Mogibacterium kristiansenii but it still did not exhibit a CCL correlation. Loggerhead cloacal communities are a promising source of novel Campilobacterota Members of the Campilobacterota phyla, particularly Arcobacteriaceae , Campylobacteraceae , and Helicobacteraceae , have recently been found to form unique, cold-adapted communities in ectothermic reptiles [ 54 ]. As expected, and based on their physiology and lifestyle, the Arcobacter genus, which can thrive at atmospheric oxygen levels and prefers lower temperatures, was present in all sample sites. However, it was more abundant in oral than cloacal samples and was rarely detected in tank water. The Helicobacter and Campylobacter genera, which are vertebrate-associated, were observed in cloacal and occasionally oral samples. Notably, one adult male (ID057) showed a higher prevalence of Helicobacter , reaching up to 20% relative abundance in the cloaca, represented by a single ASV assigned as Helicobacter sp. and not found in any other sample. This suggests a potential overgrowth or infection despite the relatively good clinical status of the individual observed at the time. Therefore, like other reptiles, loggerhead sea turtles could serve as a valuable source of previously undiscovered cold-adapted Campylobacter and Helicobacter species, as well as mucosal Arcobacter species. Oral bacterial communities harbour distinct taxa and could reflect recent diet In oral samples, the genera Truepera and Halioglobus showed differential abundance. Trueperaceae , a relatively new family, includes one isolate Truepera radiovictrix , known for radiation resistance and thriving in extreme conditions like other Deinococci members [ 55 ]. Truepera was also a dominant part of the oral microbiota in splendid japalure lizards [ 56 ], but its role and functions in reptile oral microbiomes remain unclear. Tolerance to extreme environments and ability to use diverse carbon sources may allow Truepera spp. to outcompete other taxa on reptilian oral mucosa. The genus Halioglobus is typically found in seawater, marine sediments, and has been associated with dinoflagellate blooms and starving green-lipped mussels [ 57 , 58 ]. We have previously reported Halioglobus in oral samples of loggerhead sea turtles [ 25 ]. Halioglobus bacteria likely derive from loggerhead prey such as mussels or oysters rather than being an intrinsic property of sea turtle mucosal surfaces, given the limited information on host-associated Halioglobus . Similarly, the high relative abundance of the genus Exiguobacterium in oral and cloacal samples of one juvenile loggerhead (ID069) sampled upon admission may indicate recent feeding, as some Exiguobacterium species are commonly found on shrimp or algae [ 59 – 61 ]. Carapace microbiota is distinct, yet can harbour taxa specific to oral or cloacal microbiota The carapace and skin of loggerhead sea turtles harbour diverse microbial biofilms, rich in prokaryotes, microeukaryotes, and macroeukaryotes like barnacles and algae [ 3 , 28 ]. These surface microbial communities vary with the turtle's geographical location and the sampled anatomical site [ 28 , 29 ]. They can be considered as microbial reservoirs and “diversity hotspots” in otherwise scarce environments [ 62 , 63 ]. In our study, we found expectedly distinct microbial communities in the carapace, oral mucosa, and cloaca, although many microbial taxa were present across all body sites, including potential zoonotic pathogens primarily from the cloaca. Oral and cloacal samples shared several differentially abundant microbial taxa ( Tenacibaculum , Cardiobacteraceae , Campylobacter ), suggesting co-inhabitation of the gastrointestinal tract. The carapace microbiota differed significantly from tank water, with indication of transfer of certain taxa from carapaces to tank water or vice versa. Taxa like Alteromonadaceae and Colwelliaceae ( Thalassotalea ), differentially abundant on carapaces in this study, were prominent in enclosure tank water in prior studies that did not examine carapace bacterial communities [ 24 ], possibly originating from captive turtles' carapaces. The implications of the interplay between microbes from different body sites on loggerhead sea turtles in their natural habitats and during captivity are not yet clear. However, it is essential to consider surface microbiota and potential opportunistic pathogens, especially when rehabilitating severely injured and possibly immunocompromised individuals. Fungal communities of loggerhead cloaca are highly heterogeneous and diverse Fungal communities in loggerhead sea turtles' cloaca and tank water exhibit high variability among individuals, with greater diversity observed in tank water. In this study, we could not attribute differences in the composition and structure of cloacal mycobiota to the turtles' age, sex, or hospitalization status, possibly due to the limited sample size per sampling site and condition assessed. Conversely, captive juvenile green turtles displayed more consistent mycobiota richness and diversity across various sampling sites and health conditions, unaffected by environmental fungi [ 31 ]. The taxonomic composition of cloacal and tank water fungal phyla in our study aligns with previously reported marine fungi groups found in green sea turtle faeces [ 31 ], as well as marine algicolous fungi, sediments, and sponges [ 67 ]. Due to the lower resolution of the ITS2 gene marker and many unassigned fungal ASVs beyond the family level, this study offers just a general overview and serves as a foundation for further exploration of specific groups of interest. We sporadically detected pathogenic fungal genera [ 18 ], with nine pathogenic genera found in both cloaca and tank water. Among these, Fusarium species (family Nectriaceae ) are recognized sea turtle pathogens linked to reduced hatchling success [ 68 ]. Our study identified Fusarium oxysporum (a known pathogen), Fusarium neocosmosporellium , and Fusarium waltergamsii , not previously reported as sea turtle pathogens but related to known pathogenic species in the Fusarium solani species complex [ 18 , 69 ]. Fusarium ASVs were relatively less abundant, except in one sample where they reached 8%. However, some ASVs assigned to the Nectriaceae genus may belong to Fusarium species as ITS region can be insufficient in detecting Fusarium species [ 70 ], potentially affecting our reported abundance of pathogenic fungi in cloacal and tank water samples. The origin of these fungi—whether they are metabolically active and intrinsic to the sampled turtle population or introduced from the environment as spores or through food—is unclear. The impact of these fungi on the host, the interaction with the turtle's immune system and physiology, and their potential host association remain unknown. Many fungal ASVs detected in this study belong to primarily terrestrial taxa, suggesting possible terrestrial sources during rehabilitation or a lack of marine fungal sequences in taxonomy databases. Additionally, numerous reads were assigned only as "Fungi," indicating either undiscovered fungal taxa, lack of representative sequences or possible turtle host origin. Low biomass of samples is a potential limitation to interpreting results Microbial composition results should be interpreted with caution due to low biomass collected with swabs and fewer fungal cells compared to bacterial cells in vertebrate guts [ 64 ]. Negative control (sterile water) sequenced with bacterial primers showed a small number of reads that were also detected in low-read samples, indicating potential contamination during DNA extraction and sequencing specifically for samples with low biomass (e.g., kitome) [ 65 , 66 ]. Surprisingly, the negative control sequenced with fungal primers had significantly more reads than the bacterial negative control, containing numerous ASVs also found in cloacal and tank water samples. Although the community structures of cloacal and tank water samples differed from the negative control, indicating genuine fungal communities rather than random contaminants, the high number of reads from seemingly low-biomass samples or the "empty" negative control raises concerns about our sample handling and sequencing approach. To our knowledge, no studies addressed fungal contamination in DNA extraction kits as they do for prokaryotes, making it challenging to pinpoint the exact source of this fungal DNA. For future studies we suggest including additional negative control samples at various sampling and processing stages when investigating as of yet undescribed gut-associated fungal communities. Conclusion Loggerhead sea turtle-associated microbial communities are crucial for understanding the biology of these endangered reptiles and supporting conservation. In this study, we examined bacterial and fungal communities in juvenile, subadult, and adult loggerhead sea turtles. Our findings revealed distinct microbial communities in the carapace, cloaca, and oral mucosa, with characteristic taxa for each site and shared taxa between cloacal and oral samples (e.g., Tenacibaculum , Moraxellaceae , Cardiobacteriaceae , and Campylobacter ). Cloacal bacterial communities exhibited decreasing diversity and changing composition with turtle age, likely due to shifts in diet as juveniles develop stronger bite force and diving capabilities. Microbial exchange with the environment appears to occur, particularly from turtles to tank water, especially from the carapace. Fungal communities in cloaca and tank water displayed high heterogeneity across individuals, with no age or clinical patterns, possibly due to limited samples and low fungal biomass in cloacal samples. Loggerhead sea turtles host complex microbial communities, including potential bacterial and fungal pathogens, which pose risks to handlers or general public as changing turtle behaviour leads to increased human-turtle interactions. Despite growing research on loggerhead microbiomes, defining a healthy microbiome beyond bacteria remains challenging. Future research should prioritize establishing a description of healthy loggerhead microbiomes at different developmental stages (from eggs and hatchlings to juveniles and adults) to enhance conservation practices and explore potential probiotics and prebiotics for addressing their current and future needs. Declarations Acknowledgments For the Croatian sample collection, we are thankful to Milena Mičić, Karin Gobić Medica and the rest of the staff from the Marine Turtle Rescue Center (Aquarium Pula). For the Italian collection of the samples and recruitment of turtles we are thankful to Pasquale Salvemini of the “Centro di recupero tartarughe marine WWF Molfetta”. Ethical approval Sampling was performed in accordance with the 1975 Declaration of Helsinki, as revised in 2013 and the applicable national laws. The sampling at the Sea Turtle Clinic (Bari, Italy) was conducted with the permission of the Department of Veterinary Medicine Animal Ethic Committee (Authorization # 4/19), while sampling in Croatia was done in accordance with the authorization of the Marine Turtle Rescue Center by the Ministry of Environment and Energy of the Republic of Croatia. Data availability Sequencing data with non-biological sequences removed is available at EMBL ENA at accessions PRJEB62752, and PRJEB68216 for 16S rRNA gene and PRJEB62762 for ITS2 region sequences. Epizoic samples’ sequencing data obtained from Kanjer et al. [27] and used in this study can be found at ENA under accession PRJEB51458. Complete code and instructions for processing of the sequencing data and subsequent statistical analyses, results, and data visualizations are available at Github (https://github.com/kl-fil/2023-Filek_et_al._TBIOME_project) and ZENODO data depository (doi:10.5281/zenodo.8054926). Competing interests The authors declare that there are no competing interests. Funding This work has been fully supported by the Croatian Science Foundation under the project number UIP-2017-05-5635. The work of doctoral student K. Filek has been fully supported by the “Young Researchers’ Career Development Project – Training of Doctoral Students” of the Croatian Science Foundation funded by the European Union from the European Social Fund. Contributions KF and SB concepted and designed the study; AT, MC, AB and SB collected the samples; MŽ, LK and KF carried out the laboratory work; KF and BV conducted the bioinformatics, statistical analyses, and data visualization and interpretation; KF wrote the first draft of the manuscript; all authors revised the paper and approved the final version of the manuscript. References McFall-Ngai M, Hadfield MG, Bosch TCG, Carey HV, Domazet-Lošo T, Douglas AE, Dubilier N, Eberl G, Fukami T, Gilbert SF, Hentschel U, King N, Kjelleberg S, Knoll AH, Kremer N, Mazmanian SK, Metcalf JL, Nealson K, Pierce NE, Rawls JF, Reid A, Ruby EG, Rumpho M, Sanders JG, Tautz D, Wernegreen JJ (2013) Animals in a bacterial world, a new imperative for the life sciences. Proc Natl Acad Sci 110:3229. https://doi.org/10.1073/pnas.1218525110 Henry LP, Bruijning M, Forsberg SKG, Ayroles JF (2021) The microbiome extends host evolutionary potential. Nat Commun 12:5141. https://doi.org/10.1038/s41467-021-25315-x Robinson NJ, Pfaller JB (2022) Sea Turtle Epibiosis: Global Patterns and Knowledge Gaps. Front Ecol Evol 10:844021. https://doi.org/10.3389/fevo.2022.844021 Robinson NJ, Majewska R, Lazo-Wasem EA, Nel R, Paladino FV, Rojas L, Zardus JD, Pinou T (2016) Epibiotic diatoms are universally present on all sea turtle species. PLoS ONE 11:e0157011–e0157011. https://doi.org/10.1371/journal.pone.0157011 Abdelrhman KFA, Bacci G, Mancusi C, Mengoni A, Serena F, Ugolini A (2016) A First Insight into the Gut Microbiota of the Sea Turtle Caretta caretta. Front Microbiol 7:1–5. https://doi.org/10.3389/fmicb.2016.01060 Kuschke SG (2022) What lives on and in the sea turtle? A literature review of sea turtle bacterial microbiota. Anim Microbiome 4:52. https://doi.org/10.1186/s42523-022-00202-y Stanford CB, Iverson JB, Rhodin AGJ, Paul van Dijk P, Mittermeier RA, Kuchling G, Berry KH, Bertolero A, Bjorndal KA, Blanck TEG, Buhlmann KA, Burke RL, Congdon JD, Diagne T, Edwards T, Eisemberg CC, Ennen JR, Forero-Medina G, Frankel M, Fritz U, Gallego-García N, Georges A, Gibbons JW, Gong S, Goode EV, Shi HT, Hoang H, Hofmeyr MD, Horne BD, Hudson R, Juvik JO, Kiester RA, Koval P, Le M, Lindeman PV, Lovich JE, Luiselli L, McCormack TEM, Meyer GA, Páez VP, Platt K, Platt SG, Pritchard PCH, Quinn HR, Roosenburg WM, Seminoff JA, Shaffer HB, Spencer R, Van Dyke JU, Vogt RC, Walde AD (2020) Turtles and Tortoises Are in Trouble. Curr Biol 30:R721–R735. https://doi.org/10.1016/j.cub.2020.04.088 Mazaris AD, Schofield G, Gkazinou C, Almpanidou V, Hays GC (2017) Global sea turtle conservation successes. Sci Adv 3:e1600730–e1600730. https://doi.org/10.1126/sciadv.1600730 Mazaris AD, Dimitriadis C, Papazekou M, Schofield G, Doxa A, Chatzimentor A, Turkozan O, Katsanevakis S, Lioliou A, Abalo-Morla S, Aksissou M, Arcangeli A, Attard V, El Hili HA, Atzori F, Belda EJ, Ben Nakhla L, Berbash AA, Bjorndal KA, Broderick AC, Camiñas JA, Candan O, Cardona L, Cetkovic I, Dakik N, de Lucia GA, Dimitrakopoulos PG, Diryaq S, Favilli C, Fortuna CM, Fuller WJ, Gallon S, Hamza A, Jribi I, Ben Ismail M, Kamarianakis Y, Kaska Y, Korro K, Koutsoubas D, Lauriano G, Lazar B, March D, Marco A, Minotou C, Monsinjon JR, Naguib NM, Palialexis A, Piroli V, Sami K, Sönmez B, Sourbès L, Sözbilen D, Vandeperre F, Vignes P, Xanthakis M, Köpsel V, Peck MA (2023) Priorities for Mediterranean marine turtle conservation and management in the face of climate change. J Environ Manage 339:117805. https://doi.org/10.1016/j.jenvman.2023.117805 Hird SM (2017) Evolutionary Biology Needs Wild Microbiomes. Front Microbiol 8:725. https://doi.org/10.3389/fmicb.2017.00725 Ebani VV (2023) Bacterial Infections in Sea Turtles. Vet Sci 10:333. https://doi.org/10.3390/vetsci10050333 Dallas JW, Warne RW (2023) Captivity and Animal Microbiomes: Potential Roles of Microbiota for Influencing Animal Conservation. Microb Ecol 85:820–838. https://doi.org/10.1007/s00248-022-01991-0 IUCN (2015) Caretta caretta (Mediterranean subpopulation): Casale, P.: The IUCN Red List of Threatened Species 2015: e.T83644804A83646294 Blasi MF, Migliore L, Mattei D, Rotini A, Thaller MC, Alduina R (2020) Antibiotic Resistance of Gram-Negative Bacteria from Wild Captured Loggerhead Sea Turtles. Antibiotics 9:162–162. https://doi.org/10.3390/antibiotics9040162 Pace A, Dipineto L, Fioretti A, Hochscheid S (2019) Loggerhead sea turtles as sentinels in the western Mediterranean: antibiotic resistance and environment-related modifications of Gram-negative bacteria. Mar Pollut Bull 149:110575–110575. https://doi.org/10.1016/j.marpolbul.2019.110575 Pace A, Rinaldi L, Ianniello D, Borrelli L, Cringoli G, Fioretti A, Hochscheid S, Dipineto L (2019) Gastrointestinal investigation of parasites and Enterobacteriaceae in loggerhead sea turtles from Italian coasts. BMC Vet Res 15:1–9. https://doi.org/10.1186/s12917-019-2113-4 Capri FC, Prazzi E, Casamento G, Gambino D, Cassata G, Alduina R (2023) Correlation Between Microbial Community and Hatching Failure in Loggerhead Sea Turtle Caretta caretta. Microb Ecol. https://doi.org/10.1007/s00248-023-02197-8 Gleason FH, Allerstorfer M, Lilje O (2020) Newly emerging diseases of marine turtles, especially sea turtle egg fusariosis (SEFT), caused by species in the Fusarium solani complex (FSSC). Mycology 11:184–194. https://doi.org/10.1080/21501203.2019.1710303 Trotta A, Cirilli M, Marinaro M, Bosak S, Diakoudi G, Ciccarelli S, Paci S, Buonavoglia D, Corrente M (2021) Detection of multi-drug resistance and AmpC β-lactamase/extended-spectrum β-lactamase genes in bacterial isolates of loggerhead sea turtles (Caretta caretta) from the Mediterranean Sea. Mar Pollut Bull 164:112015. https://doi.org/10.1016/j.marpolbul.2021.112015 Trotta A, Marinaro M, Sposato A, Galgano M, Ciccarelli S, Paci S, Corrente M (2021) Antimicrobial Resistance in Loggerhead Sea Turtles (Caretta caretta): A Comparison between Clinical and Commensal Bacterial Isolates. Animals 11:2435. https://doi.org/10.3390/ani11082435 Alduina R, Gambino D, Presentato A, Gentile A, Sucato A, Savoca D, Filippello S, Visconti G, Caracappa G, Vicari D, Arculeo M (2020) Is Caretta Caretta a Carrier of Antibiotic Resistance in the Mediterranean Sea? Antibiotics 9:116–116. https://doi.org/10.3390/antibiotics9030116 Gambino D, Persichetti MF, Gentile A, Arculeo M, Visconti G, Currò V, Caracappa G, Crucitti D, Piazza A, Mancianti F, Nardoni S, Vicari D, Caracappa S (2020) First data on microflora of loggerhead sea turtle ( Caretta caretta ) nests from the coastlines of Sicily. Biol Open 9:bio045252–bio045252. https://doi.org/10.1242/bio.045252 Arizza V, Vecchioni L, Caracappa S, Sciurba G, Berlinghieri F, Gentile A, Persichetti MF, Arculeo M, Alduina R (2019) New insights into the gut microbiome in loggerhead sea turtles Caretta caretta stranded on the Mediterranean coast. Plos One 14:e0220329–e0220329. https://doi.org/10.1371/journal.pone.0220329 Biagi E, D’Amico F, Soverini M, Angelini V, Barone M, Turroni S, Rampelli S, Pari S, Brigidi P, Candela M (2019) Faecal bacterial communities from Mediterranean loggerhead sea turtles (Caretta caretta). Environ Microbiol Rep 11:361–371. https://doi.org/10.1111/1758-2229.12683 Filek K, Trotta A, Gračan R, Di Bello A, Corrente M, Bosak S (2021) Characterization of oral and cloacal microbial communities of wild and rehabilitated loggerhead sea turtles (Caretta caretta). Anim Microbiome 3:59. https://doi.org/10/gmptgh Biagi E, Musella M, Palladino G, Angelini V, Pari S, Roncari C, Scicchitano D, Rampelli S, Franzellitti S, Candela M (2021) Impact of Plastic Debris on the Gut Microbiota of Caretta caretta From Northwestern Adriatic Sea. Front Mar Sci 8:637030. https://doi.org/10.3389/fmars.2021.637030 Scheelings TF, Moore RJ, Van TTH, Klaassen M, Reina RD (2020) The gut bacterial microbiota of sea turtles differs between geographically distinct populations. Endanger Species Res 42:95–108. https://doi.org/10.3354/esr01042 Kanjer L, Filek K, Mucko M, Majewska R, Gračan R, Trotta A, Panagopoulou A, Corrente M, Di Bello A, Bosak S (2022) Surface microbiota of Mediterranean loggerhead sea turtles unraveled by 16S and 18S amplicon sequencing. Front Ecol Evol 10:907368. https://doi.org/10.3389/fevo.2022.907368 Blasi MF, Rotini A, Bacci T, Targusi M, Ferraro GB, Vecchioni L, Alduina R, Migliore L (2021) On Caretta caretta ’s shell: first spatial analysis of micro- and macro-epibionts on the Mediterranean loggerhead sea turtle carapace. Mar Biol Res 17:762–774. https://doi.org/10.1080/17451000.2021.2016840 Scheelings TF, Moore RJ, Van TTH, Klaassen M, Reina RD (2020) Microbial symbiosis and coevolution of an entire clade of ancient vertebrates: the gut microbiota of sea turtles and its relationship to their phylogenetic history. Anim Microbiome 2:17–17. https://doi.org/10.1186/s42523-020-00034-8 Guo Y, Chen H, Liu P, Wang F, Li L, Ye M, Zhao W, Chen J (2022) Microbial composition of carapace, feces, and water column in captive juvenile green sea turtles with carapacial ulcers. Front Vet Sci 9:. https://doi.org/10.3389/fvets.2022.1039519 Trevelline BK, Fontaine SS, Hartup BK, Kohl KD (2019) Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices. Proc R Soc B Biol Sci 286:20182448. https://doi.org/10.1098/rspb.2018.2448 Bjorndal KA, Bolten AB, Martins HR (2000) Somatic growth model of juvenile loggerhead sea turtles Caretta caretta: duration of pelagic stage. Mar Ecol Prog Ser 202:265–272. https://doi.org/10.3354/meps202265 Pinou T, Domenech F, Majewska R, Pfaller JB, Zardus JD, Robinson NJ (2019) Standardizing Sea Turtle Epibiont Sampling : Outcomes of the Epibiont Workshop at the 37 th International Sea Turtle Symposium. Mar Turt Newsl. https://doi.org/10.13140/RG.2.2.31843.81440 Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, Glöckner FO (2013) Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res 41:1–11. https://doi.org/10.1093/nar/gks808 White TJ, Bruns T, Lee S, Taylor J (1990) AMPLIFICATION AND DIRECT SEQUENCING OF FUNGAL RIBOSOMAL RNA GENES FOR PHYLOGENETICS. In: PCR Protocols. Elsevier, pp 315–322 Andrews S (2010) FastQC: a quality control tool for high throughput sequencing data Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, Bai Y, Bisanz JE, Bittinger K, Brejnrod A, Brislawn CJ, Brown CT, Callahan BJ, Caraballo-Rodríguez AM, Chase J, Cope EK, Da Silva R, Diener C, Dorrestein PC, Douglas GM, Durall DM, Duvallet C, Edwardson CF, Ernst M, Estaki M, Fouquier J, Gauglitz JM, Gibbons SM, Gibson DL, Gonzalez A, Gorlick K, Guo J, Hillmann B, Holmes S, Holste H, Huttenhower C, Huttley GA, Janssen S, Jarmusch AK, Jiang L, Kaehler BD, Kang KB, Keefe CR, Keim P, Kelley ST, Knights D, Koester I, Kosciolek T, Kreps J, Langille MGI, Lee J, Ley R, Liu YX, Loftfield E, Lozupone C, Maher M, Marotz C, Martin BD, McDonald D, McIver LJ, Melnik AV, Metcalf JL, Morgan SC, Morton JT, Naimey AT, Navas-Molina JA, Nothias LF, Orchanian SB, Pearson T, Peoples SL, Petras D, Preuss ML, Pruesse E, Rasmussen LB, Rivers A, Robeson MS, Rosenthal P, Segata N, Shaffer M, Shiffer A, Sinha R, Song SJ, Spear JR, Swafford AD, Thompson LR, Torres PJ, Trinh P, Tripathi A, Turnbaugh PJ, Ul-Hasan S, van der Hooft JJJ, Vargas F, Vázquez-Baeza Y, Vogtmann E, von Hippel M, Walters W, Wan Y, Wang M, Warren J, Weber KC, Williamson CHD, Willis AD, Xu ZZ, Zaneveld JR, Zhang Y, Zhu Q, Knight R, Caporaso JG (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 37:852–857. https://doi.org/10.1038/s41587-019-0209-9 Lozupone C, Lladser ME, Knights D, Stombaugh J, Knight R (2011) UniFrac: An effective distance metric for microbial community comparison. ISME J 5:169–172. https://doi.org/10.1038/ismej.2010.133 Gloor GB, Macklaim JM, Pawlowsky-Glahn V, Egozcue JJ (2017) Microbiome datasets are compositional: And this is not optional. Front Microbiol 8:. https://doi.org/10.3389/fmicb.2017.02224 Martino C, Morton JT, Marotz CA, Thompson LR, Tripathi A, Knight R, Zengler K (2019) A Novel Sparse Compositional Technique Reveals Microbial Perturbations. mSystems 4:1–13. https://doi.org/10.1128/mSystems.00016-19 Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Szoecs E, Wagner H (2020) vegan: Community Ecology Package Arbizu PM (2017) pairwiseAdonis: Pairwise Multilevel Comparison using Adonis Peddada S, Lin H (2023) Multi-group Analysis of Compositions of Microbiomes with Covariate Adjustments and Repeated Measures. In Review Lin H, Peddada SD (2020) Analysis of compositions of microbiomes with bias correction. Nat Commun 11:3514. https://doi.org/10.1038/s41467-020-17041-7 Bisanz JE (2018) qiime2R: Importing QIIME2 artifacts and associated data into R sessions Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019) Welcome to the tidyverse. J Open Source Softw 4:1686. https://doi.org/10.21105/joss.01686 Wickham, Hadley (2016) ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York Reese AT, Dunn RR (2018) Drivers of Microbiome Biodiversity: A Review of General Rules, Feces, and Ignorance. mBio 9:10.1128/mbio.01294-18. https://doi.org/10.1128/mbio.01294-18 Mariani G, Bellucci F, Cocumelli C, Raso C, Hochscheid S, Roncari C, Nerone E, Recchi S, Di Giacinto F, Olivieri V, Pulsoni S, Matiddi M, Silvestri C, Ferri N, Renzo LD (2023) Dietary Preferences of Loggerhead Sea Turtles (Caretta caretta) in Two Mediterranean Feeding Grounds: Does Prey Selection Change with Habitat Use throughout Their Life Cycle? Anim Open Access J MDPI 13:654. https://doi.org/10.3390/ani13040654 Casale P, Abbate G, Freggi D, Conte N, Oliverio M, Argano R (2008) Foraging ecology of loggerhead sea turtles Caretta caretta in the central Mediterranean Sea: evidence for a relaxed life history model. Mar Ecol Prog Ser 372:265–276. https://doi.org/10.3354/meps07702 Hao W, Gerdts G, Peplies J, Wichels A (2015) Bacterial communities associated with four ctenophore genera from the German Bight (North Sea). FEMS Microbiol Ecol 91:1–11. https://doi.org/10.1093/femsec/fiu006 Mabrok M, Algammal AM, Sivaramasamy E, Hetta HF, Atwah B, Alghamdi S, Fawzy A, Avendaño-Herrera R, Rodkhum C (2023) Tenacibaculosis caused by Tenacibaculum maritimum: Updated knowledge of this marine bacterial fish pathogen. Front Cell Infect Microbiol 12:1068000. https://doi.org/10.3389/fcimb.2022.1068000 Gilbert MJ, Duim B, Zomer AL, Wagenaar JA (2019) Living in Cold Blood: Arcobacter, Campylobacter, and Helicobacter in Reptiles. Front Microbiol 10: Albuquerque L, Simões C, Nobre MF, Pino NM, Battista JR, Silva MT, Rainey FA, de Costa MS (2005) Truepera radiovictrix gen. nov., sp. nov., a new radiation resistant species and the proposal of Trueperaceae fam. nov. FEMS Microbiol Lett 247:161–169. https://doi.org/10.1016/j.femsle.2005.05.002 Tian Z, Pu H, Cai D, Luo G, Zhao L, Li K, Zou J, Zhao X, Yu M, Wu Y, Yang T, Guo P, Hu X (2022) Characterization of the bacterial microbiota in different gut and oral compartments of splendid japalure (Japalura sensu lato). BMC Vet Res 18:205. https://doi.org/10.1186/s12917-022-03300-w Hattenrath-Lehmann TK, Jankowiak J, Koch F, Gobler CJ (2019) Prokaryotic and eukaryotic microbiomes associated with blooms of the ichthyotoxic dinoflagellate Cochlodinium (Margalefidinium) polykrikoides in New York, USA, estuaries. PLOS ONE 14:e0223067. https://doi.org/10.1371/journal.pone.0223067 Li S, Young T, Archer S, Lee K, Alfaro AC (2023) Gut microbiome resilience of green-lipped mussels, Perna canaliculus, to starvation. Int Microbiol. https://doi.org/10.1007/s10123-023-00397-3 Kasana RC, Pandey CB (2018) Exiguobacterium: an overview of a versatile genus with potential in industry and agriculture. Crit Rev Biotechnol 38:141–156. https://doi.org/10.1080/07388551.2017.1312273 Liu F, Li Y, He W, Wang W, Zheng J, Zhang D (2021) Exiguobacterium algae sp. nov. and Exiguobacterium qingdaonense sp. nov., two novel moderately halotolerant bacteria isolated from the coastal algae. Antonie Van Leeuwenhoek 114:1399–1406. https://doi.org/10.1007/s10482-021-01594-8 Cong M, Jiang Q, Xu X, Huang L, Su Y, Yan Q (2017) The complete genome sequence of Exiguobacterium arabatum W‐01 reveals potential probiotic functions. MicrobiologyOpen 6:e00496. https://doi.org/10.1002/mbo3.496 Keller AG, Apprill A, Lebaron P, Robbins J, Romano TA, Overton E, Rong Y, Yuan R, Pollara S, Whalen KE (2021) Characterizing the culturable surface microbiomes of diverse marine animals. FEMS Microbiol Ecol 97:. https://doi.org/10/gmvjt3 Filek K, Lebbe L, Willems A, Chaerle P, Vyverman W, Žižek M, Bosak S (2022) More than just hitchhikers: a survey of bacterial communities associated with diatoms originating from sea turtles. FEMS Microbiol Ecol 98:fiac104. https://doi.org/10.1093/femsec/fiac104 Lavrinienko A, Scholier T, Bates ST, Miller AN, Watts PC (2021) Defining gut mycobiota for wild animals: a need for caution in assigning authentic resident fungal taxa. Anim Microbiome 3:75. https://doi.org/10.1186/s42523-021-00134-z Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, Turner P, Parkhill J, Loman NJ, Walker AW (2014) Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol 12:87. https://doi.org/10.1186/s12915-014-0087-z Grahn N, Olofsson M, Ellnebo-Svedlund K, Monstein H-J, Jonasson J (2003) Identification of mixed bacterial DNA contamination in broad-range PCR amplification of 16S rDNA V1 and V3 variable regions by pyrosequencing of cloned amplicons. FEMS Microbiol Lett 219:87–91. https://doi.org/10.1016/S0378-1097(02)01190-4 Jones EBG, Pang K-L, Abdel-Wahab MA, Scholz B, Hyde KD, Boekhout T, Ebel R, Rateb ME, Henderson L, Sakayaroj J, Suetrong S, Dayarathne MC, Kumar V, Raghukumar S, Sridhar KR, Bahkali AHA, Gleason FH, Norphanphoun C (2019) An online resource for marine fungi. Fungal Divers 96:347–433. https://doi.org/10.1007/s13225-019-00426-5 Cafarchia C, Paradies R, Figueredo LA, Iatta R, Desantis S, Di Bello AVF, Zizzo N, van Diepeningen AD (2020) Fusarium spp. in Loggerhead Sea Turtles (Caretta caretta): From Colonization to Infection. Vet Pathol 57:139–146. https://doi.org/10.1177/0300985819880347 Geiser DM, Al-Hatmi AMS, Aoki T, Arie T, Balmas V, Barnes I, Bergstrom GC, Bhattacharyya MK, Blomquist CL, Bowden RL, Brankovics B, Brown DW, Burgess LW, Bushley K, Busman M, Cano-Lira JF, Carrillo JD, Chang H-X, Chen C-Y, Chen W, Chilvers M, Chulze S, Coleman JJ, Cuomo CA, de Beer ZW, de Hoog GS, Del Castillo-Múnera J, Del Ponte EM, Diéguez-Uribeondo J, Di Pietro A, Edel-Hermann V, Elmer WH, Epstein L, Eskalen A, Esposto MC, Everts KL, Fernández-Pavía SP, da Silva GF, Foroud NA, Fourie G, Frandsen RJN, Freeman S, Freitag M, Frenkel O, Fuller KK, Gagkaeva T, Gardiner DM, Glenn AE, Gold SE, Gordon TR, Gregory NF, Gryzenhout M, Guarro J, Gugino BK, Gutierrez S, Hammond-Kosack KE, Harris LJ, Homa M, Hong C-F, Hornok L, Huang J-W, Ilkit M, Jacobs A, Jacobs K, Jiang C, Jiménez-Gasco M del M, Kang S, Kasson MT, Kazan K, Kennell JC, Kim H-S, Kistler HC, Kuldau GA, Kulik T, Kurzai O, Laraba I, Laurence MH, Lee T, Lee Y-W, Lee Y-H, Leslie JF, Liew ECY, Lofton LW, Logrieco AF, S. López-Berges M, Luque AG, Lysøe E, Ma L-J, Marra RE, Martin FN, May SR, McCormick SP, McGee C, Meis JF, Migheli Q, Mohamed Nor NMI, Monod M, Moretti A, Mostert D, Mulè G, Munaut F, Munkvold GP, Nicholson P, Nucci M, O’Donnell K, Pasquali M, Pfenning LH, Prigitano A, Proctor RH, Ranque S, Rehner SA, Rep M, Rodríguez-Alvarado G, Rose LJ, Roth MG, Ruiz-Roldán C, Saleh AA, Salleh B, Sang H, Scandiani MM, Scauflaire J, Schmale DG, Short DPG, Šišić A, Smith JA, Smyth CW, Son H, Spahr E, Stajich JE, Steenkamp E, Steinberg C, Subramaniam R, Suga H, Summerell BA, Susca A, Swett CL, Toomajian C, Torres-Cruz TJ, Tortorano AM, Urban M, Vaillancourt LJ, Vallad GE, van der Lee TAJ, Vanderpool D, van Diepeningen AD, Vaughan MM, Venter E, Vermeulen M, Verweij PE, Viljoen A, Waalwijk C, Wallace EC, Walther G, Wang J, Ward TJ, Wickes BL, Wiederhold NP, Wingfield MJ, Wood AKM, Xu J-R, Yang X-B, Yli-Mattila T, Yun S-H, Zakaria L, Zhang H, Zhang N, Zhang SX, Zhang X (2021) Phylogenomic Analysis of a 55.1-kb 19-Gene Dataset Resolves a Monophyletic Fusarium that Includes the Fusarium solani Species Complex. Phytopathology® 111:1064–1079. https://doi.org/10.1094/PHYTO-08-20-0330-LE Hoh DZ, Lin Y-F, Liu W-A, Sidique SNM, Tsai IJ (2020) Nest microbiota and pathogen abundance in sea turtle hatcheries. Fungal Ecol 47:100964. https://doi.org/10.1016/j.funeco.2020.100964 Additional Declarations No competing interests reported. Supplementary Files ESM1.docx FigS1.png Fig. S1 Fungal communities’ diversity . unweighted UniFrac PCoA plot and rAitchison PCA biplot Fig. S1 Diversity of fungal communities in cloacal and tank water samples. (a) Unweighted UniFrac PCoA (a) and robust Aitchison PCA biplot (b) with loadings as highly ranked features. Corresponding cloacal and tank water samples are connected with dashed lines. FigS2.pdf Fig. S2 Relative abundance of differentially abundant taxa for epizoic, endozoic and tank water V4 reads Fig. S2 Relative abundance [centered log ratio (clr)] of differentially abundant taxa (ANCOM-BC2, with structural zeros excluded) collapsed at species level in carapace, cloacal, oral and tank water samples. On the left side, the panel indicates in which sample site out of all sample site pairs the specific taxon is significantly differentially abundant (p-value < 0.05). Black dots indicate significance after correction for multiple testing (q-value < 0.05). The rows and columns were clustered using complete linkage method. TableS1loggerheadinfoallsamples.xlsx Table S1Extended metadata on all samples in this study TableS2clinicalconsiderations.xlsx Table S2 Clinical considerations for turtles in this study TableS3v34rawcounts.xlsx Table S3 Raw read counts for endozoic and tank water samples V34 TableS4ITS2rawcounts.xlsx Table S4 Raw read counts for cloacal and tank water samples ITS2 TableS5v4rawcounts.xlsx Table S5 Raw read counts for epizoic, endozoic, and tank water samples V4 Cite Share Download PDF Status: Published Journal Publication published 30 May, 2024 Read the published version in Microbial Ecology → Version 1 posted Editorial decision: Revision requested 03 Mar, 2024 Reviews received at journal 19 Feb, 2024 Reviewers agreed at journal 31 Jan, 2024 Reviewers invited by journal 25 Jan, 2024 Submission checks completed at journal 24 Jan, 2024 Editor assigned by journal 24 Jan, 2024 First submitted to journal 24 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3893610","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":269625027,"identity":"cfddad3c-9456-45f9-b845-ea370cb122a1","order_by":0,"name":"Klara Filek","email":"","orcid":"","institution":"University of Zagreb","correspondingAuthor":false,"prefix":"","firstName":"Klara","middleName":"","lastName":"Filek","suffix":""},{"id":269625031,"identity":"cb17a459-dba2-4d2b-8244-77fd79442105","order_by":1,"name":"Borna Branimir Vuković","email":"","orcid":"","institution":"Rudjer Boskovic Institute","correspondingAuthor":false,"prefix":"","firstName":"Borna","middleName":"Branimir","lastName":"Vuković","suffix":""},{"id":269625032,"identity":"a475e8dc-55ad-4690-9981-6ca50cb9aeb4","order_by":2,"name":"Marta Žižek","email":"","orcid":"","institution":"Rudjer Boskovic Institute","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"","lastName":"Žižek","suffix":""},{"id":269625033,"identity":"9ab321e5-1118-4b92-8e2f-dec1ed868b5f","order_by":3,"name":"Lucija Kanjer","email":"","orcid":"","institution":"University of Zagreb","correspondingAuthor":false,"prefix":"","firstName":"Lucija","middleName":"","lastName":"Kanjer","suffix":""},{"id":269625034,"identity":"7c03c087-d333-4583-8c07-61ca763f3afe","order_by":4,"name":"Adriana Trotta","email":"","orcid":"","institution":"University of Bari Aldo Moro","correspondingAuthor":false,"prefix":"","firstName":"Adriana","middleName":"","lastName":"Trotta","suffix":""},{"id":269625035,"identity":"a031d94c-305d-4965-b8b3-f0b17db5afb9","order_by":5,"name":"Antonio di Bello","email":"","orcid":"","institution":"University of Bari Aldo Moro","correspondingAuthor":false,"prefix":"","firstName":"Antonio","middleName":"di","lastName":"Bello","suffix":""},{"id":269625036,"identity":"e22c89ac-fb49-4d09-a0d9-bce8fbab1ab3","order_by":6,"name":"Marialaura Corrente","email":"","orcid":"","institution":"University of Bari Aldo Moro","correspondingAuthor":false,"prefix":"","firstName":"Marialaura","middleName":"","lastName":"Corrente","suffix":""},{"id":269625037,"identity":"e8e1d528-fb52-4d01-8a03-68f64530ace5","order_by":7,"name":"Sunčica Bosak","email":"data:image/png;base64,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","orcid":"","institution":"University of Zagreb","correspondingAuthor":true,"prefix":"","firstName":"Sunčica","middleName":"","lastName":"Bosak","suffix":""}],"badges":[],"createdAt":"2024-01-24 09:29:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3893610/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3893610/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00248-024-02388-x","type":"published","date":"2024-05-30T08:03:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":50745395,"identity":"a589080c-6bdb-4eeb-8e6f-16e3a09b0577","added_by":"auto","created_at":"2024-02-06 17:01:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":230914,"visible":true,"origin":"","legend":"\u003cp\u003eLocations and body measurements of loggerhead sea turtles with corresponding IDs. (a) Map of locations where loggerhead sea turtles were found prior to transport to rehabilitation centres and sampling. (b) Relationship of loggerheads’ weight in kilograms and curved carapace length in centimetres (CCL). The sex of each turtle is indicated by shape [female triangle, male square, and not determined (ND) circle], while age range was determined as follows: juveniles ≤59.9 cm, subadults 60-69.9 cm, adults ≥70 cm (b).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/40d8621090199888bde4f628.png"},{"id":50746757,"identity":"81515c14-d09a-40ac-b830-eb5037ed36e3","added_by":"auto","created_at":"2024-02-06 17:09:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":227075,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial community structure and diversity in loggerhead sea turtles’ cloacal, oral, and tank water samples. (a, b) Alpha diversity boxplots with sample density for Faith’s phylogenetic diversity (a) and Shannon’s index (b) per sample site. (c) Pearson’s correlation between Faith’s phylogenetic diversity and curved carapace length (CCL). (d) Robust Aitchison PCA biplot with highly ranked features as loadings. Cloacal samples are depicted by diamonds, oral samples by circles, and tank water by inverted triangle shapes (d).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/15aa4389730735adf7460288.png"},{"id":50745396,"identity":"449b5b63-4349-4a3a-a230-23f972145155","added_by":"auto","created_at":"2024-02-06 17:01:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":361788,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential abundance analysis by ANCOM-BC2 for ASVs (a) and taxa collapsed to species level (b) in cloacal, oral and tank water samples. Only differentially abundant taxa in oral or cloacal sample sites are shown. Sample site abbreviations are “Clo” for cloaca; “Orl” for oral; “TW” for tank water samples. The first sample site listed in sample site pairs was used as a denominator for log fold change (LFC) calculations in pairwise testing, thus the LFC value for that body site being \u0026lt; 0. Single asterisk (*) indicates significant differential abundance (p-value \u0026lt; 0.05), while double asterisk (**) indicates significance after adjusting for multiple testing (q-value \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/0521f848cbab41913891add3.png"},{"id":50746755,"identity":"404b87cd-adc4-4ca1-9059-abe247c6c171","added_by":"auto","created_at":"2024-02-06 17:09:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":273140,"visible":true,"origin":"","legend":"\u003cp\u003eStructure and composition of fungal microbial communities in cloaca and tank water samples. (a, b) Alpha diversity boxplots with sample density for Faith’s phylogenetic diversity (a) and Shannon’s index (b) per sample site. (c) Differential abundance analysis by ANCOM-BC2 for taxa collapsed to species level in cloacal and tank water samples. Cloacal sample site was used as a denominator for log fold change (LFC) calculations in pairwise testing, thus the cloacal LFC values being \u0026lt; 0. Single asterisk (*) indicates significant differential abundance (p-value \u0026lt; 0.05). (d) Relative abundance of fungal phyla in cloacal and tank water samples present above 1% in at least one sample. Sample IDs ending with “C” belong to cloacal samples, while Sample IDs ending with “W” belong to tank water samples.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/fcd24c8a11d0803e7c013a24.png"},{"id":50746758,"identity":"ab0f898e-8820-4841-8590-a11cdf0b0418","added_by":"auto","created_at":"2024-02-06 17:09:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":253777,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial community structure and diversity in loggerhead sea turtles’ carapace, cloacal, oral, and tank water samples. (a, b) Alpha diversity boxplots with sample density for Faith’s phylogenetic diversity (a) and Shannon’s index (b) per sample site. (c) Robust Aitchison PCA biplot with highly ranked features as loadings. Cloacal samples are depicted by diamonds, oral samples by circles, carapace samples by squares, and tank water by inverted triangle shapes (d).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/48d78efe8b49905f58ef8856.png"},{"id":50745401,"identity":"aafa5b5f-5263-4798-a950-1e86d4ac1653","added_by":"auto","created_at":"2024-02-06 17:01:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":470538,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential abundance analysis by ANCOM-BC2 (with structural zeros excluded) for ASVs in carapace, cloacal, oral and tank water samples. Sample site abbreviations are “Car” for carapace, “Clo” for cloaca; “Orl” for oral; “TW” for tank water samples. The first sample site listed in sample site pairs was used as a denominator for log fold change (LFC) calculations in pairwise testing, thus the LFC value for that body site being \u0026lt; 0. Single asterisk (*) indicates differential abundance (p-value \u0026lt; \u0026nbsp;0.05), while double asterisk (**) indicates significance after adjusting for multiple testing (q-value \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/180820a77295dd8c76dae680.png"},{"id":59086415,"identity":"b565a55b-da93-42e0-af79-abe54a2c04fe","added_by":"auto","created_at":"2024-06-26 08:03:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2533329,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/81720c50-d72c-42c3-98ac-f0b1dbc300b4.pdf"},{"id":50745403,"identity":"a6ec6123-3117-4057-a6f3-9354b7b3bbd2","added_by":"auto","created_at":"2024-02-06 17:01:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":685014,"visible":true,"origin":"","legend":"","description":"","filename":"ESM1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/65e33f28e198e19ddc00e01d.docx"},{"id":50745399,"identity":"08df7f89-80eb-4af9-9bcc-66d907d4617c","added_by":"auto","created_at":"2024-02-06 17:01:23","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":201317,"visible":true,"origin":"","legend":"\u003cp\u003eFig. S1 Fungal communities’ diversity . unweighted UniFrac PCoA plot and rAitchison PCA biplot\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S1 \u003c/strong\u003eDiversity of fungal communities in cloacal and tank water samples. (a) Unweighted UniFrac PCoA (a) and robust Aitchison PCA biplot (b) with loadings as highly ranked features. Corresponding cloacal and tank water samples are connected with dashed lines.\u003c/p\u003e","description":"","filename":"FigS1.png","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/309640f03aeb21a8f3cb75d1.png"},{"id":50745405,"identity":"f2320f90-e652-4c48-a925-f4a6b10942d4","added_by":"auto","created_at":"2024-02-06 17:01:24","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1298222,"visible":true,"origin":"","legend":"\u003cp\u003eFig. S2 Relative abundance of differentially abundant taxa for epizoic, endozoic and tank water V4 reads\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. S2 \u003c/strong\u003eRelative abundance [centered log ratio (clr)] of differentially abundant taxa (ANCOM-BC2, with structural zeros excluded) collapsed at species level in carapace, cloacal, oral and tank water samples. On the left side, the panel indicates in which sample site out of all sample site pairs the specific taxon is significantly differentially abundant (p-value \u0026lt; 0.05). Black dots indicate significance after correction for multiple testing (q-value \u0026lt; 0.05). The rows and columns were clustered using complete linkage method.\u003c/p\u003e","description":"","filename":"FigS2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/781e0b69961d28ad8c8b04b4.pdf"},{"id":50746754,"identity":"e0e678fb-7635-4527-8f08-b2d17393561c","added_by":"auto","created_at":"2024-02-06 17:09:23","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":33258,"visible":true,"origin":"","legend":"\u003cp\u003eTable S1Extended metadata on all samples in this study\u003c/p\u003e","description":"","filename":"TableS1loggerheadinfoallsamples.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/3f8a70088e26d594f702c113.xlsx"},{"id":50748702,"identity":"db58ed79-954f-4c07-9152-c2034b2a27fd","added_by":"auto","created_at":"2024-02-06 17:17:23","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":18002,"visible":true,"origin":"","legend":"\u003cp\u003eTable S2 Clinical considerations for turtles in this study\u003c/p\u003e","description":"","filename":"TableS2clinicalconsiderations.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/03b47820f1a253639ab0a0df.xlsx"},{"id":50745407,"identity":"a9b466ce-e6b4-4985-89d7-016dbb62037a","added_by":"auto","created_at":"2024-02-06 17:01:24","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":4037961,"visible":true,"origin":"","legend":"\u003cp\u003eTable S3 Raw read counts for endozoic and tank water samples V34\u003c/p\u003e","description":"","filename":"TableS3v34rawcounts.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/1681544661932d3252bda42b.xlsx"},{"id":50746759,"identity":"1b029f42-d38e-446a-b23d-f92025de0734","added_by":"auto","created_at":"2024-02-06 17:09:24","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":2037958,"visible":true,"origin":"","legend":"\u003cp\u003eTable S4 Raw read counts for cloacal and tank water samples ITS2\u003c/p\u003e","description":"","filename":"TableS4ITS2rawcounts.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/501edc65c8fb48faab08f496.xlsx"},{"id":50745406,"identity":"bd60d50e-1e17-4aae-93f9-cd53496f0fb9","added_by":"auto","created_at":"2024-02-06 17:01:24","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":4815071,"visible":true,"origin":"","legend":"\u003cp\u003eTable S5 Raw read counts for epizoic, endozoic, and tank water samples V4\u003c/p\u003e","description":"","filename":"TableS5v4rawcounts.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3893610/v1/b042ec14eec27b26272764f3.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Loggerhead Sea Turtles as Hosts of Diverse Bacterial and Fungal Communities","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMicrobial communities associated with animal hosts play crucial roles in various aspects of the host\u0026rsquo;s development, physiology, immune response, metabolism, and reproduction, and may have an impact on the host\u0026rsquo;s evolutionary potential [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. While the importance of sea turtle epibiosis with macro-epibionts (\u0026gt;\u0026thinsp;1 mm) such as barnacles has long been recognized [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], research on the microbial epibionts and endobionts of sea turtles has only recently gained attention [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Sea turtles hold a unique ecological role as keystone species, connecting terrestrial and coastal habitats, but they are also highly vulnerable to anthropogenic threats, such as climate change, disruption of feeding and breeding habitats, egg poaching, and accidental bycatch [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. To lessen some of the pressure sea turtles face today, global conservation efforts have focused on safeguarding female turtles and nesting areas, and rehabilitating injured turtles [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Motivated by the aim of enhancing the rehabilitation and conservation of wild animals and their associated microbiomes, the studies of sea turtle gut, skin, egg, and nest microbiomes have become a forefront in sea turtle conservation research, building upon cultivation-based and pathogen-oriented research in the veterinary domain [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLoggerhead sea turtles (\u003cem\u003eCaretta caretta\u003c/em\u003e) are a widely distributed species and are classified as vulnerable by the IUCN Red List of threatened species [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, the Mediterranean subpopulation of loggerheads is considered to be of least concern due to successful conservation efforts [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Currently, loggerhead sea turtles\u0026rsquo; microbiota is the second most studied, preceded only by green turtles (\u003cem\u003eChelonia mydas\u003c/em\u003e) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Previous studies that used culture-dependent approaches have identified most common pathogens associated with mucosal surfaces, skin lesions (such as bacterial families \u003cem\u003eAeromonadaceae\u003c/em\u003e, \u003cem\u003ePseudomonadaceae\u003c/em\u003e, \u003cem\u003eEnterobacteriaceae\u003c/em\u003e), and hatchling failure (\u003cem\u003eFusarium\u003c/em\u003e spp.), with the presence of antibiotic resistance genes indicating loggerheads as sentinels of antibiotic pollution in the Mediterranean [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18 CR19 CR20 CR21\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Recent investigations using next-generation sequencing approaches to study the loggerhead microbiota shed light on the bacterial community structure and composition of the gastrointestinal tract [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], the impact of rehabilitation on mucosal bacteriomes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], the effects of plastic pollution on the gut bacteria [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], variations in microbial communities driven by localities [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] or turtle anatomy [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], and host-microbial coevolution patterns [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. On the other hand, the fungal communities associated with marine reptiles, including sea turtles, have received limited attention using cultivation-independent approaches, despite the vulnerability of sea turtles to infections caused by \u003cem\u003eFusarium\u003c/em\u003e spp. during early development [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Recent work by Guo et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] provided initial insights into the fungal communities found on carapace (healthy and ulcerated), in faeces, and in the seawater of green turtle juveniles undergoing rehabilitation, however, comprehensive surveys of endobiotic fungal communities in loggerhead sea turtles have not yet been conducted. Given the ecological significance of loggerhead sea turtles in the Mediterranean basin ecosystem, their role as sentinels for pollution, and their potential to act as vectors for zoonotic diseases, a comprehensive approach including eukaryotic microorganisms is necessary to understand the loggerhead sea turtle microbiota. This knowledge will contribute to the advancement of current conservation practices and future microbial stewardship efforts [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe objective of this study was to investigate the bacterial and fungal communities associated with loggerhead sea turtles found in the Adriatic Sea. We analysed the bacterial communities in the cloacal, oral, and enclosure samples as well as fungal communities of cloacal and enclosure tank water samples using amplicon sequencing targeting the V3-V4 (V34) region of 16S rRNA gene and the ITS2 region of nuclear ribosomal genes, respectively. Furthermore, when available, we analysed the bacterial communities of carapace biofilm samples corresponding to turtles in this study out of which some were previously analysed as a part of our earlier study on sea-turtle epibiosis [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. By combining these datasets, we provide a comprehensive overview of the environmental, surface, and internal microbiota of the loggerhead turtles, establishing a baseline for future holobiont approaches to studying the loggerhead sea turtles.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eLoggerhead sea turtle sampling\u003c/h2\u003e \u003cp\u003eLoggerhead sea turtles investigated in this study were found at various locations along the Adriatic Sea coast from 2019 to 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea) and transported to two locations where the sampling was conducted; at Sea Turtle Clinic (STC) of the Department of Veterinary Medicine of University of Bari \u0026ldquo;Aldo Moro\u0026rdquo; in Italy and the Sea Turtle Rescue Center Aquarium Pula in Croatia. The turtles were sampled immediately upon their arrival to the rehabilitation centres or during/after rehabilitation, and prior to release (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Turtles were classified as juveniles, subadult and adults according to [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and sex determination was based on observable physical characteristics when possible (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Additional information about sampling procedures and the loggerhead population surveyed in this study can be found in Supplementary Methods and Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe endozoic samples were collected from cloacal and oral cavities in triplicates by sterile synthetic swabs (Aptaca Nuova) as described in Filek et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. When available, enclosure tank water was collected in sterile containers, vacuum filtered on 0.2 \u0026micro;m sterile Whatmann polycarbonate membrane filters (Sigma-Aldrich) and stored in 2 ml tubes in 96% EtOH. All samples were stored at -20 C until DNA extraction and further processing. Additionally, corresponding epizoic carapace biofilm samples were obtained by randomly brushing the entire carapace using a toothbrush (Dentalux Classic, hard, Lidl) according to [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and the collected material was resuspended in 96% EtOH, and stored at -20 C (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Each endozoic sequencing sample ID that is referred to in this manuscript has a 16S or ITS prefix, sampling event number, and suffix corresponding to sampling site: C - cloaca, O - oral cavity, W - tank water; for example, sample ID ITS0084C represents cloacal sample of fungal ITS2 sequences for sampling event 0084 (turtle ID010; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Epizoic samples have a TB prefix and numbering unrelated to sampling event.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInformation about loggerhead sea turtles and their corresponding endozoic (16S rRNA gene and fungal ITS2 region) and epizoic (16S rRNA gene) samples (V4 \u0026ndash; Kanjer et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], V34 \u0026ndash; this study). The turtles were retrieved at various locations in the Adriatic Sea and were admitted to Sea Turtle Rescue Center Aquarium Pula (Croatia) unless indicated otherwise (\u003csup\u003eT\u003c/sup\u003e Tyrrhenian Sea; \u003csup\u003eSTC\u003c/sup\u003e The Sea Turtle Clinic at University of Bari, Italy). The abbreviations are as follows: Clo \u0026ndash; cloaca, Orl \u0026ndash; oral cavity, TW \u0026ndash; tank water, Car \u0026ndash; carapace, NA \u0026ndash; not available, ND \u0026ndash; not determined.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTurtle ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTurtle name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSampling event\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eEndozoic 16S/ITS2 sample presence (+) or absence (-) \u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEpizoic 16S \u003c/p\u003e \u003cp\u003esample ID \u003c/p\u003e \u003cp\u003e(region)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge range\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOrl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCar\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMerry Fisher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB139 (V4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSubadult\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eŽal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB115 (V4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJuvenile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSamba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB117 (V4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAdult\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eID057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAngelo\u003csup\u003eSTC\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdult\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB119 (V4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKanooh\u003csup\u003eSTC\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB145 (V4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJuvenile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKanfus\u003csup\u003eSTC\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJuvenile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFuton\u003csup\u003eSTC\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB149 (V4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJuvenile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCosmyn\u003csup\u003eSTC\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB151 (V4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSubadult\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarvin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB155 (V4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJuvenile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRyan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB157 (V4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJuvenile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eID093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eElla Ravka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB159 (V34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSubadult\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eID096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMaro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB167 (V34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSubadult\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFreewings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJuvenile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaksimus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB175 (V34)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJuvenile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKarlo Albano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB215 (V34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAdult\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOliver Raul\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB217 (V34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJuvenile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMartin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTB219 (V34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJuvenile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLuka Amadeo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAdult\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e*\u003c/sup\u003eEach sample ID has a 16S or ITS prefix, sampling event number, and suffix corresponding to sampling site: C - cloaca, O - oral cavity, W - tank water; for example, sample ID ITS0084C represents cloacal sample of fungal ITS2 sequences for sampling event 0084.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e**\u003c/sup\u003e Carapace sample was collected at a different sampling event (a month prior to endozoic sampling).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction and sequencing\u003c/h2\u003e \u003cp\u003eTotal DNA from swabs and filters was extracted using the DNeasy PowerSoil kit (Qiagen) following the manufacturer\u0026rsquo;s instructions with several modifications: (1) the samples were incubated in C1 solution at 65 C for one hour, (2) instead of bead beating PowerBead Tubes were vortexed horizontally for 10 min at maximum speed, and (3) all downstream incubation times at 2\u0026ndash;8\u0026deg;C were increased to 15 min.\u003c/p\u003e \u003cp\u003eThe methods used for epizoic carapace biofilm samples that were sequenced for V4 region (ID010 \u0026ndash; ID074) are described by Kanjer et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The DNA from biofilm scrapings (ID093 \u0026ndash; ID122) analysed only in this study was extracted via DNeasy PowerLyzer PowerSoil extraction kit (Qiagen) following the manufacturer\u0026rsquo;s instructions and modified as follows: 1) after addition of C1 solution the samples were incubated at 70\u0026deg;C for 10 minutes; 2) bead beating was performed at 30 Hz for 1 minute in TissueLyzer Retsch Qiagen; 3) 50 \u0026micro;l of C6 solution was used for DNA elution and incubated for 5 minutes at room temperature prior to centrifugation. Nuclease-free water (W4502 Sigma-Aldrich) was used as the negative control for the DNA extraction step and was processed using the DNA extraction kit in parallel to all the samples. The quality and quantity of extracted DNA was evaluated by BioSpec-nano (Shimadzu).\u003c/p\u003e \u003cp\u003eThe extracted DNA from both endozoic and epizoic samples was stored at -20 C and sent for Illumina MiSeq v3 300x2 bp paired-end sequencing to Microsynth, Switzerland. Primers used for sequencing the V34 region of 16S rRNA gene were 341F and 805R [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], and primers for fungal ITS2 region of the nuclear ribosomal gene were ITS3 and ITS4 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatics and statistics\u003c/h2\u003e \u003cp\u003eThe obtained sequences had non-biological sequences trimmed by the sequencing facility and checked for quality with FastQC [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Sequencing data is available at EMBL ENA at accessions PRJEB62752, and PRJEB68216 for 16S rRNA gene, PRJEB62762 for ITS2 region sequences and from Kanjer et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] PRJEB51458. The sequences were imported and analysed in QIIME 2 (versions 2021.8 and 2023.2) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStatistical analyses were performed within QIIME 2 environment and with R. Alpha diversity indices, including Shannon\u0026rsquo;s entropy, Pielou\u0026rsquo;s evenness, Faith\u0026rsquo;s phylogenetic diversity, and observed ASVs, were calculated via q2-diversity plugin. The Kruskal-Wallis rank sum test was employed to determine differences between selected groups, followed by post-hoc pairwise comparisons using Wilcoxon rank sum exact test. For beta diversity analyses, rarefied data (sequencing depth determined by alpha rarefaction curves) were explored using the q2-diversity plugin with Bray-Curtis, Jaccard, unweighted UniFrac, weighted UniFrac distances [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Compositional data analysis on non-rarefied datasets was performed by calculating robust Aitchison distances using the q2-deicode plugin or the R package vegan v.2.6-4 [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Principal coordinates analysis (PCoA) was conducted on Bray-Curtis, Jaccard, and all UniFrac distances, while principal components analysis was performed for robust Aitchison (rPCA) using q2-diversity and q2-deicode, respectively. To assess the relative impact of factors (age range, sex, and duration of rehabilitation) on microbial communities, a multi-way permutational multivariate analysis of variance (Adonis2 PERMANOVA) with 9999 permutations was employed (Anderson, 2001) in R by using vegan v.2.6-4 and pairwiseAdonis v.0.4.1 packages [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Resulting p-values from all pairwise tests were adjusted using the Benjamini-Hochberg false-discovery rate (FDR) correction for multiple comparisons (reported as q-values). Differential abundance analysis was used to identify differentially abundant (DA) features in sample site pairs by using the ANCOMBC package \u0026ldquo;ancombc2\u0026rdquo; function in R [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Default parameters were used and pairwise testing was enabled (with Holm\u0026rsquo;s method for adjusting p-values, reported as q-values), except for DA testing in V4-trimmed sequences where the \u0026ldquo;struc_zero\u0026rdquo; was set to \u0026ldquo;TRUE\u0026rdquo; to exclude structural zeros based on sampling sites. Log fold change (LFC) indicates the scale of differential abundance between differentially abundant features. Features with p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were reported as differentially abundant, and q-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as significantly differentially abundant.\u003c/p\u003e \u003cp\u003eData exploration and visualizations were conducted by using R v.4.3.0 in RStudio (R Core Team 2023) with packages listed above and in Supplement and qiime2R v.0.99.6 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], tidyverse v2.0.0 [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], ggplot2 v3.4.2 [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], Microsoft Excel, and Adobe Illustrator. Additional details of sample processing and data analyses are available in the Supplementary Methods.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eEndozoic and tank water bacterial communities\u003c/h2\u003e \u003cp\u003eAltogether, 50 endozoic and water samples (plus one negative control) were sequenced, and 7,110,067 high quality sequences were obtained (median frequency per sample was 107,522, min. 2, max. 911,443). Denoising yielded a total of 11,105 ASVs. After filtering mitochondrial and chloroplast sequences, the number of ASVs decreased to 10,946. Forty-three samples yielded enough high-quality reads (at minimum sequencing depth above 10,000) for downstream analyses (19/21 cloacal, 16/20 oral, and 8/9 tank water samples).\u003c/p\u003e \u003cp\u003eThe highest number of observed features (OF) and phylogenetic diversity (Faith\u0026rsquo;s PD) was found in tank water samples (median OF\u0026thinsp;=\u0026thinsp;603, IQR\u0026thinsp;=\u0026thinsp;450; median Faith\u0026rsquo;s PD\u0026thinsp;=\u0026thinsp;42.8, IQR\u0026thinsp;=\u0026thinsp;53.9), followed by oral samples (median OF 473, IQR\u0026thinsp;=\u0026thinsp;428; median Faith\u0026rsquo;s PD 40.2, IQR\u0026thinsp;=\u0026thinsp;26.2), and cloacal samples (median OF\u0026thinsp;=\u0026thinsp;308, IQR\u0026thinsp;=\u0026thinsp;235; median Faith\u0026rsquo;s PD\u0026thinsp;=\u0026thinsp;28.4, IQR\u0026thinsp;=\u0026thinsp;20) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). ASV richness and evenness (Shannon\u0026rsquo;s index) was highest in oral samples (median\u0026thinsp;=\u0026thinsp;6.28, IQR\u0026thinsp;=\u0026thinsp;1.33), followed by cloacal (median\u0026thinsp;=\u0026thinsp;5.62, IQR\u0026thinsp;=\u0026thinsp;1.66), and tank water samples (median\u0026thinsp;=\u0026thinsp;5.44, IQR\u0026thinsp;=\u0026thinsp;1.67) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Alpha diversity showed significant differences among sample sites (Kruskal-Wallis rank sum test) for OF and Faith\u0026rsquo;s PD (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while pairwise sample site comparisons (Wilcoxon rank sum test) showed differences between cloaca vs. oral samples and cloaca vs. tank water (q-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Shannon\u0026rsquo;s index showed weak statistical difference among samples sites (p-value\u0026thinsp;=\u0026thinsp;0.04). Pearson correlation on alpha diversity indices against size of the turtle (CCL) in individual sample site groups showed strong negative correlation between cloacal samples and OF and Faith\u0026rsquo;s PD (R = -0.67, p-value\u0026thinsp;=\u0026thinsp;0.002 and R = -0.59, p-value\u0026thinsp;=\u0026thinsp;0.007, respectively) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), while Shannon\u0026rsquo;s index showed weaker negative correlation with CCL (R = -0.53, p-value\u0026thinsp;=\u0026thinsp;0.021). Oral and tank water alpha diversity did not show any correlation effects. Further, within cloacal samples, differences were detected (Kruskal-Wallis p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in age range (OF, pairwise Wilcox: adult vs. juvenile q-value\u0026thinsp;=\u0026thinsp;0.024; Faith\u0026rsquo;s PD, pairwise: adult vs. juvenile q-value\u0026thinsp;=\u0026thinsp;0.024) and sex of the turtles (OF, pairwise Wilcox: male vs. ND q-value\u0026thinsp;=\u0026thinsp;0.004; Faith\u0026rsquo;s PD, pairwise: male vs. ND q-value\u0026thinsp;=\u0026thinsp;0.018), which are directly related to turtles\u0026rsquo; size.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBacterial communities among samples sites differed based on PERMANOVA for Bray-Curtis (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.09, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.001), Jaccard (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.08, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.001), unweighted and weighted UniFrac (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.12, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.001; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.13, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.001, respectively), and robust Aitchison distances (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.24, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.002). Pairwise PERMANOVA detected differences between all sample site pairs for most beta diversity metrics except robust Aitchison where only cloaca vs. tank water and tank water vs. oral samples pairs were significantly different (Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;\u0026le;\u0026thinsp;0.002). Highly ranked ASVs impacting the distribution of samples on rPCA biplot were assigned to Gammaproteobacteria, order Oceanospirillales, \u003cem\u003eShewanella algae\u003c/em\u003e, \u003cem\u003eVibrio\u003c/em\u003e sp., and NS3a marine group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). Within cloacal samples, significant differences in bacterial communities were detected between adults vs. juveniles (Bray-Curtis, Jaccard, and unweighted UniFrac Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and ND vs. males (all distances except robust Aitchison Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;\u0026lt;\u0026thinsp;0.05) or females (Jaccard and weighted UniFrac Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In oral samples there were differences between early vs. late hospitalization duration (all distances except robust Aitchison Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and early vs. mid (weighted UniFrac Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;\u0026lt;\u0026thinsp;0.05) hospitalization durations.\u003c/p\u003e \u003cp\u003eCloacal bacterial communities differed between age groups based on PERMANOVA for Bray-Curtis (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.15, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.018), Jaccard (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.14, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.008) and unweighted UniFrac distance (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.16, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.013). Pairwise PERMANOVA showed significant differences only between adults and juveniles for all above-mentioned diversity measures (Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;\u0026le;\u0026thinsp;0.009). The differences between adults and juveniles are observed in community composition and structure as well: phylum Verrucomicrobiota appears more often in juveniles, juveniles also have higher RA of Rhodobacterales (Alphaproteobacteria), Cardiobacterales (Gammaproteobacteria), Kineosporiales (Actinobacteriota), Oligoflexales (Bdellovibrionota), \u003cem\u003eArcobacteraceae\u003c/em\u003e (Campylobacterales), and more Flavobacteriales (Bacteroidota) than adults. On the other hand, adults carry more Bacteroidales (Bacteroidota), Pasteurellales (Gammaproteobacteria), \u003cem\u003eHelicobacteraceae\u003c/em\u003e and \u003cem\u003eCampylobacteraceae\u003c/em\u003e (Campylobacterales), and \u003cem\u003eLeptotrichiaceae\u003c/em\u003e (Fusobacteriales). The low number of samples (\u0026le;\u0026thinsp;10) in each age group prevented us from further differential abundance analyses. Detailed taxonomic composition of bacterial communities found in oral, cloacal and tank water samples is reported in Supplementary Results, Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e with additional visualizations available at Github.\u003c/p\u003e \u003cp\u003eDifferential abundance analysis detected 33 significantly DA features (post adjusting for multiple testing) out of which two were differentially abundant in cloaca (ASV467 \u003cem\u003eRhodobacteraceae\u003c/em\u003e and ASV4007 \u003cem\u003eShewanella algae\u003c/em\u003e), and three in oral samples (ASV9794 \u003cem\u003eTruepera\u003c/em\u003e sp., ASV6166 and ASV467 both belonging to \u003cem\u003eRhodobacteraceae\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Tank water had 28 DA ASVs when tested against cloaca or oral samples, most of which belonged to typical marine taxa (\u003cem\u003eCryomorphaceae\u003c/em\u003e, NS3a marine group, SAR406 clade, \u003cem\u003eRhodobacteraceae\u003c/em\u003e, \u003cem\u003eNitrincolaceae\u003c/em\u003e, etc.). When collapsed to species level, 75 significantly DA taxa were detected, out of which 13 in cloaca and 15 in oral samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Depending on the tested sample site pair several features would be DA in both oral and cloacal samples when compared to tank water e.g., genera \u003cem\u003eMarinifilum, Tenacibaculum\u003c/em\u003e, and \u003cem\u003eLabrenzia\u003c/em\u003e, members of \u003cem\u003eCardiobacteriaceae\u003c/em\u003e and \u003cem\u003eComamonadaceae\u003c/em\u003e families (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEndozoic and tank water fungal communities\u003c/h2\u003e \u003cp\u003eOverall, 29 samples (plus one negative control) were sequenced, and 2,208,729 high quality sequences were obtained (median frequency per sample was 69,203, min. 11,722, max. 150,142). Denoising yielded a total of 9,547 ASVs. Based on alpha rarefaction curves, 27 samples yielded enough high-quality reads (at minimum sequencing depth at 25,000 reads) for downstream statistical analyses requiring rarefied data (19/20 cloacal, and 8/9 tank water samples). All samples except negative control were used in compositional data analyses.\u003c/p\u003e \u003cp\u003eTank water samples had significantly higher number of observed features and phylogenetic diversity (median\u0026thinsp;=\u0026thinsp;674, IQR\u0026thinsp;=\u0026thinsp;97.8; Faith\u0026rsquo;s PD median\u0026thinsp;=\u0026thinsp;98.0, IQR\u0026thinsp;=\u0026thinsp;10.5) than cloacal samples (median\u0026thinsp;=\u0026thinsp;509, IQR\u0026thinsp;=\u0026thinsp;372, Faith\u0026rsquo;s PD median\u0026thinsp;=\u0026thinsp;66.6, IQR\u0026thinsp;=\u0026thinsp;51.7) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) based on Kruskal-Wallis rank sum test (OF p-value\u0026thinsp;=\u0026thinsp;0.008; Faith\u0026rsquo;s PD p-value\u0026thinsp;=\u0026thinsp;0.007). Shannon\u0026rsquo;s diversity was not detected as significantly different between sample sites (tank water median\u0026thinsp;=\u0026thinsp;8.66, IQR\u0026thinsp;=\u0026thinsp;1.31; cloaca median\u0026thinsp;=\u0026thinsp;6.76, IQR\u0026thinsp;=\u0026thinsp;2.58) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). There were no significant differences in alpha diversity values within cloacal or tank water fungal communities when tested for age range, sex, or rehabilitation duration. The only beta diversity metric that showed significant differences between tank water and cloaca was unweighted UniFrac (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.06, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.042). Unweighted UniFrac PCoA showed unclear sample groupings, however, there is a separation of cloacal and corresponding tank water samples on PCA1 axis (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ea, corresponding samples connected with dashed lines). Compositional data analysis rPCA did not show clear separation of samples sites, and top ranked ASVs belonged to \u003cem\u003ePreussia flanaganii\u003c/em\u003e, genus \u003cem\u003eTetracladium\u003c/em\u003e, order \u003cem\u003eXylariales\u003c/em\u003e, genus \u003cem\u003eRhizoctonia\u003c/em\u003e, and family \u003cem\u003eNectriaceae\u003c/em\u003e (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eb). When collapsed to species level, cloacal and tank water samples each had five differentially abundant fungal taxa detected. In cloacal samples DA taxa were \u003cem\u003eLeptodiscella\u003c/em\u003e, \u003cem\u003eElaphomyces\u003c/em\u003e, \u003cem\u003eSclerocleista\u003c/em\u003e, \u003cem\u003eGliomastix\u003c/em\u003e, \u003cem\u003eThelephora\u003c/em\u003e; and in tank water they were \u003cem\u003eCladosporium\u003c/em\u003e, unidentified Leotiomycetes, unidentified Sordariomycetes (Chaetosphaerilaes), \u003cem\u003eNectria\u003c/em\u003e, and \u003cem\u003eHumicola\u003c/em\u003e - although none of them were statistically significant after correction for multiple testing (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Cloacal and tank water fungal communities were represented mostly by phyla Ascomycota (average RA\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation in cloaca and tank water\u0026thinsp;=\u0026thinsp;57\u0026thinsp;\u0026plusmn;\u0026thinsp;15% and 53\u0026thinsp;\u0026plusmn;\u0026thinsp;9%, respectively), Basidiomycota (19\u0026thinsp;\u0026plusmn;\u0026thinsp;9% and 22\u0026thinsp;\u0026plusmn;\u0026thinsp;3%), Glomeromycota (7\u0026thinsp;\u0026plusmn;\u0026thinsp;6% and 10\u0026thinsp;\u0026plusmn;\u0026thinsp;12%), Mortierellomycota (2\u0026thinsp;\u0026plusmn;\u0026thinsp;2% and 3\u0026thinsp;\u0026plusmn;\u0026thinsp;2%) unidentified Fungi (13\u0026thinsp;\u0026plusmn;\u0026thinsp;20% and 11\u0026thinsp;\u0026plusmn;\u0026thinsp;7%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). Detailed taxonomic composition of fungal communities found in cloacal and tank water samples is reported in Supplementary Results and Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEpizoic and endozoic bacterial communities\u003c/h2\u003e \u003cp\u003eAfter trimming epizoic, endozoic, and tank water sequences to V4 region of 16S rRNA gene (65 samples in total) and denoising, 10,072,866 high quality sequences were merged across all sequencing events (median frequency per sample was 126,629, min. 0, max. 946,183) and yielded 13,263 ASVs. Due to reduced resolution after trimming the longer V34 region to shorter V4 region, the number of ASVs for cloacal, oral and tank water samples was expectedly lower (7,725 in V4 vs. 11,105 in V34 sequences).\u003c/p\u003e \u003cp\u003e Carapace samples had the highest median species richness and diversity (OF median 732, IQR\u0026thinsp;=\u0026thinsp;420, Faith\u0026rsquo;s PD median\u0026thinsp;=\u0026thinsp;45.7, IQR\u0026thinsp;=\u0026thinsp;25.2; median Shannon\u0026rsquo;s index\u0026thinsp;=\u0026thinsp;5.94, IQR\u0026thinsp;=\u0026thinsp;2.22), which was followed by tank water, oral and cloacal samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). The differences between sample sites\u0026rsquo; alpha diversity were detected as statistically significant (Kruskal-Wallis rank sum test), however pairwise comparisons showed differences only in Faith\u0026rsquo;s phylogenetic diversity and OF: between cloaca and all other sample sites (except tank water based on OF), oral cavity and carapace. All beta diversity metrics showed significant differences between body sites for Bray-Curtis (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.13, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.001), Jaccard (R2\u0026thinsp;=\u0026thinsp;0.10, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.001), unweighted and weighted UniFrac (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.16, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.001; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.18, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.001, respectively), and robust Aitchison distances (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.09, Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;=\u0026thinsp;0.001). Pairwise PERMANOVA detected differences between all sample site pairs (Pr(\u0026gt;\u0026thinsp;F)\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Highly ranked ASVs impacting the distribution of samples on rPCA biplot belonged to \u003cem\u003ePseudoalteromonas\u003c/em\u003e sp., \u003cem\u003eVibrio\u003c/em\u003e sp., \u003cem\u003eShewanella\u003c/em\u003e sp., uncultured \u003cem\u003eSaccharospirillaceae\u003c/em\u003e, uncultured \u003cem\u003eMarinifilum\u003c/em\u003e and uncultured \u003cem\u003eCardiobacteriaceae\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). The taxonomic composition of endozoic samples and tank water using the V4 sequences resembled the one detected with V34 and it is reported in Table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e. Additional information on taxonomic composition of epizoic bacterial communities in carapace samples is reported in Supplementary Results.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDifferential abundance analysis on ASVs (structural zeros excluded) detected 17 significantly DA ASVs across all sample sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e). A member of \u003cem\u003eRhodobacteraceae\u003c/em\u003e family (v4ASV8861) and \u003cem\u003eHalioglobus\u003c/em\u003e sp. (v4ASV11062) were consistently DA in oral samples while the same goes for \u003cem\u003eCardiobacterium\u003c/em\u003e sp. (v4ASV10814) and a member of \u003cem\u003eEnterobacteriaceae\u003c/em\u003e family (v4ASV11383) in cloaca. In carapace samples a member of \u003cem\u003eFlavobacteriaceae\u003c/em\u003e family (v4ASV2446), cyanobacteria \u003cem\u003eLeptolyngbya\u003c/em\u003e sp. (v4ASV4472), \u003cem\u003eAhrensia\u003c/em\u003e sp. (v4ASV8480), \u003cem\u003eSphingomonadaceae\u003c/em\u003e (v4ASV9910), \u003cem\u003eErythrobacter\u003c/em\u003e sp. (v4ASV9994), \u003cem\u003eGammaproteobacteria\u003c/em\u003e (v4ASV10111), \u003cem\u003eAlteromonas\u003c/em\u003e sp. (v4ASV10327), \u003cem\u003eArenicella\u003c/em\u003e sp. (v4ASV10634), \u003cem\u003ePsychrobacter\u003c/em\u003e sp. (v4ASV12017) and \u003cem\u003eVibrio\u003c/em\u003e sp. (v4ASV12307) were DA relative to other sample sites, while \u003cem\u003eMarinomonas\u003c/em\u003e sp. (v4ASV11704) was DA abundant in carapace tested against endozoic samples, but not tank water. In tank water a member of \u003cem\u003eFlavobacteriaceae\u003c/em\u003e (v4ASV2446) and NS3a marine group (v4ASV2817) were consistently DA (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Differential abundance analysis on taxa collapsed to species level is reported in Supplementary Results and Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides an overview of the bacterial and fungal communities inhabiting oral and cloacal environments of loggerhead sea turtles. Additionally, we aimed to investigate bacterial communities in carapace samples in relation to the gastrointestinal tract and tank water to explore possible connections between two habitats. The carapace exhibited the highest bacterial diversity, followed by oral samples, influenced by the tank water environment, and then cloacal samples. Each sampling site had distinct microbial communities and cloacal bacterial diversity negatively correlated with turtle size and age. Conversely, fungal communities in the cloaca were distinct from tank water and showed high heterogeneity among individual turtles, with no discernible patterns related to age or sex.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCloacal bacterial diversity and structure changes with the turtle age\u003c/h2\u003e \u003cp\u003eSimilarly to previous studies on cloacal microbiota in Adriatic loggerhead sea turtles, we observed changes in bacterial richness, diversity, and structure, negatively correlating with loggerheads' CCL and, consequently, their age [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. According to research on vertebrate gut microbiomes, it is expected that the bacterial diversity increases with body size in animals with complex digestive systems, like ruminants, and decreases in animals with simple guts, often omnivores or carnivores [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Loggerhead sea turtles are omnivores and exhibit an ontogenetic shift from oceanic-pelagic habitats as juveniles to neritic-benthic feeding grounds as adults. However, in the Mediterranean Sea they employ an \"amphi-habitat strategy\", where juveniles, subadults and adults share feeding grounds and similar feeding behaviours [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Differences in diet, jaw size, bite force, and diving ability between juveniles and adults may result in distinct diets and digestive physiologies, potentially reflected in cloacal bacterial communities as increased richness. Studies on loggerhead diet show no significant differences in stomach contents among adults, subadults, and juveniles, but it's worth noting that softer prey like tunicates or jellyfish may not be as detectable due to easier digestion and lack of hard remains in morphology-based studies [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, juveniles exhibited higher abundance and more frequent presence of \u003cem\u003eFlavobacteriaceae\u003c/em\u003e and \u003cem\u003eTenacibaculum\u003c/em\u003e spp. in oral and cloacal samples than subadult and adult turtles. \u003cem\u003eTenacibaculum\u003c/em\u003e spp. are marine pathogens possibly carried by cnidarians and ctenophores as vectors [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], suggesting a higher proportion of soft prey in juveniles' diet. This study was conducted during non-winter months when jellyfish populations increase due to higher water temperatures potentially influencing prey availability. Adults likely have access to these prey types but also consume more challenging prey inaccessible to juveniles. Notably, in other studies \u003cem\u003eTenacibaculum\u003c/em\u003e spp. were highly abundant on loggerhead skin as well [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], indicating their propensity to inhabit marine vertebrate surfaces and gastrointestinal tracts, irrespective of animal\u0026rsquo;s diet. While in previous research the \u003cem\u003eMogibacteraceae\u003c/em\u003e family detected in faeces correlated with CCL [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], we did not detect it in our data, possibly due to different taxonomy databases being utilized (Greengenes vs. SILVA in our study). BLAST analysis showed ASVs assigned as Peptostreptococcales-Tissieralles closely related to \u003cem\u003eMogibacterium kristiansenii\u003c/em\u003e but it still did not exhibit a CCL correlation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLoggerhead cloacal communities are a promising source of novel Campilobacterota\u003c/h2\u003e \u003cp\u003eMembers of the Campilobacterota phyla, particularly \u003cem\u003eArcobacteriaceae\u003c/em\u003e, \u003cem\u003eCampylobacteraceae\u003c/em\u003e, and \u003cem\u003eHelicobacteraceae\u003c/em\u003e, have recently been found to form unique, cold-adapted communities in ectothermic reptiles [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. As expected, and based on their physiology and lifestyle, the \u003cem\u003eArcobacter\u003c/em\u003e genus, which can thrive at atmospheric oxygen levels and prefers lower temperatures, was present in all sample sites. However, it was more abundant in oral than cloacal samples and was rarely detected in tank water. The \u003cem\u003eHelicobacter\u003c/em\u003e and \u003cem\u003eCampylobacter\u003c/em\u003e genera, which are vertebrate-associated, were observed in cloacal and occasionally oral samples. Notably, one adult male (ID057) showed a higher prevalence of \u003cem\u003eHelicobacter\u003c/em\u003e, reaching up to 20% relative abundance in the cloaca, represented by a single ASV assigned as \u003cem\u003eHelicobacter\u003c/em\u003e sp. and not found in any other sample. This suggests a potential overgrowth or infection despite the relatively good clinical status of the individual observed at the time. Therefore, like other reptiles, loggerhead sea turtles could serve as a valuable source of previously undiscovered cold-adapted \u003cem\u003eCampylobacter\u003c/em\u003e and \u003cem\u003eHelicobacter\u003c/em\u003e species, as well as mucosal \u003cem\u003eArcobacter\u003c/em\u003e species.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eOral bacterial communities harbour distinct taxa and could reflect recent diet\u003c/h2\u003e \u003cp\u003eIn oral samples, the genera \u003cem\u003eTruepera\u003c/em\u003e and \u003cem\u003eHalioglobus\u003c/em\u003e showed differential abundance. \u003cem\u003eTrueperaceae\u003c/em\u003e, a relatively new family, includes one isolate \u003cem\u003eTruepera radiovictrix\u003c/em\u003e, known for radiation resistance and thriving in extreme conditions like other Deinococci members [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. \u003cem\u003eTruepera\u003c/em\u003e was also a dominant part of the oral microbiota in splendid japalure lizards [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], but its role and functions in reptile oral microbiomes remain unclear. Tolerance to extreme environments and ability to use diverse carbon sources may allow \u003cem\u003eTruepera\u003c/em\u003e spp. to outcompete other taxa on reptilian oral mucosa. The genus \u003cem\u003eHalioglobus\u003c/em\u003e is typically found in seawater, marine sediments, and has been associated with dinoflagellate blooms and starving green-lipped mussels [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. We have previously reported \u003cem\u003eHalioglobus\u003c/em\u003e in oral samples of loggerhead sea turtles [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. \u003cem\u003eHalioglobus\u003c/em\u003e bacteria likely derive from loggerhead prey such as mussels or oysters rather than being an intrinsic property of sea turtle mucosal surfaces, given the limited information on host-associated \u003cem\u003eHalioglobus\u003c/em\u003e. Similarly, the high relative abundance of the genus \u003cem\u003eExiguobacterium\u003c/em\u003e in oral and cloacal samples of one juvenile loggerhead (ID069) sampled upon admission may indicate recent feeding, as some \u003cem\u003eExiguobacterium\u003c/em\u003e species are commonly found on shrimp or algae [\u003cspan additionalcitationids=\"CR60\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCarapace microbiota is distinct, yet can harbour taxa specific to oral or cloacal microbiota\u003c/h2\u003e \u003cp\u003eThe carapace and skin of loggerhead sea turtles harbour diverse microbial biofilms, rich in prokaryotes, microeukaryotes, and macroeukaryotes like barnacles and algae [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These surface microbial communities vary with the turtle's geographical location and the sampled anatomical site [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. They can be considered as microbial reservoirs and \u0026ldquo;diversity hotspots\u0026rdquo; in otherwise scarce environments [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. In our study, we found expectedly distinct microbial communities in the carapace, oral mucosa, and cloaca, although many microbial taxa were present across all body sites, including potential zoonotic pathogens primarily from the cloaca. Oral and cloacal samples shared several differentially abundant microbial taxa (\u003cem\u003eTenacibaculum\u003c/em\u003e, \u003cem\u003eCardiobacteraceae\u003c/em\u003e, \u003cem\u003eCampylobacter\u003c/em\u003e), suggesting co-inhabitation of the gastrointestinal tract. The carapace microbiota differed significantly from tank water, with indication of transfer of certain taxa from carapaces to tank water or vice versa. Taxa like \u003cem\u003eAlteromonadaceae\u003c/em\u003e and \u003cem\u003eColwelliaceae\u003c/em\u003e (\u003cem\u003eThalassotalea\u003c/em\u003e), differentially abundant on carapaces in this study, were prominent in enclosure tank water in prior studies that did not examine carapace bacterial communities [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], possibly originating from captive turtles' carapaces. The implications of the interplay between microbes from different body sites on loggerhead sea turtles in their natural habitats and during captivity are not yet clear. However, it is essential to consider surface microbiota and potential opportunistic pathogens, especially when rehabilitating severely injured and possibly immunocompromised individuals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFungal communities of loggerhead cloaca are highly heterogeneous and diverse\u003c/h2\u003e \u003cp\u003eFungal communities in loggerhead sea turtles' cloaca and tank water exhibit high variability among individuals, with greater diversity observed in tank water. In this study, we could not attribute differences in the composition and structure of cloacal mycobiota to the turtles' age, sex, or hospitalization status, possibly due to the limited sample size per sampling site and condition assessed. Conversely, captive juvenile green turtles displayed more consistent mycobiota richness and diversity across various sampling sites and health conditions, unaffected by environmental fungi [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The taxonomic composition of cloacal and tank water fungal phyla in our study aligns with previously reported marine fungi groups found in green sea turtle faeces [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], as well as marine algicolous fungi, sediments, and sponges [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Due to the lower resolution of the ITS2 gene marker and many unassigned fungal ASVs beyond the family level, this study offers just a general overview and serves as a foundation for further exploration of specific groups of interest.\u003c/p\u003e \u003cp\u003eWe sporadically detected pathogenic fungal genera [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], with nine pathogenic genera found in both cloaca and tank water. Among these, \u003cem\u003eFusarium\u003c/em\u003e species (family \u003cem\u003eNectriaceae\u003c/em\u003e) are recognized sea turtle pathogens linked to reduced hatchling success [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Our study identified \u003cem\u003eFusarium oxysporum\u003c/em\u003e (a known pathogen), \u003cem\u003eFusarium neocosmosporellium\u003c/em\u003e, and \u003cem\u003eFusarium waltergamsii\u003c/em\u003e, not previously reported as sea turtle pathogens but related to known pathogenic species in the \u003cem\u003eFusarium solani\u003c/em\u003e species complex [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. \u003cem\u003eFusarium\u003c/em\u003e ASVs were relatively less abundant, except in one sample where they reached 8%. However, some ASVs assigned to the \u003cem\u003eNectriaceae\u003c/em\u003e genus may belong to \u003cem\u003eFusarium\u003c/em\u003e species as ITS region can be insufficient in detecting \u003cem\u003eFusarium\u003c/em\u003e species [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e], potentially affecting our reported abundance of pathogenic fungi in cloacal and tank water samples.\u003c/p\u003e \u003cp\u003eThe origin of these fungi\u0026mdash;whether they are metabolically active and intrinsic to the sampled turtle population or introduced from the environment as spores or through food\u0026mdash;is unclear. The impact of these fungi on the host, the interaction with the turtle's immune system and physiology, and their potential host association remain unknown. Many fungal ASVs detected in this study belong to primarily terrestrial taxa, suggesting possible terrestrial sources during rehabilitation or a lack of marine fungal sequences in taxonomy databases. Additionally, numerous reads were assigned only as \"Fungi,\" indicating either undiscovered fungal taxa, lack of representative sequences or possible turtle host origin.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLow biomass of samples is a potential limitation to interpreting results\u003c/h2\u003e \u003cp\u003eMicrobial composition results should be interpreted with caution due to low biomass collected with swabs and fewer fungal cells compared to bacterial cells in vertebrate guts [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Negative control (sterile water) sequenced with bacterial primers showed a small number of reads that were also detected in low-read samples, indicating potential contamination during DNA extraction and sequencing specifically for samples with low biomass (e.g., kitome) [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Surprisingly, the negative control sequenced with fungal primers had significantly more reads than the bacterial negative control, containing numerous ASVs also found in cloacal and tank water samples. Although the community structures of cloacal and tank water samples differed from the negative control, indicating genuine fungal communities rather than random contaminants, the high number of reads from seemingly low-biomass samples or the \"empty\" negative control raises concerns about our sample handling and sequencing approach. To our knowledge, no studies addressed fungal contamination in DNA extraction kits as they do for prokaryotes, making it challenging to pinpoint the exact source of this fungal DNA. For future studies we suggest including additional negative control samples at various sampling and processing stages when investigating as of yet undescribed gut-associated fungal communities.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eLoggerhead sea turtle-associated microbial communities are crucial for understanding the biology of these endangered reptiles and supporting conservation. In this study, we examined bacterial and fungal communities in juvenile, subadult, and adult loggerhead sea turtles. Our findings revealed distinct microbial communities in the carapace, cloaca, and oral mucosa, with characteristic taxa for each site and shared taxa between cloacal and oral samples (e.g., \u003cem\u003eTenacibaculum\u003c/em\u003e, \u003cem\u003eMoraxellaceae\u003c/em\u003e, \u003cem\u003eCardiobacteriaceae\u003c/em\u003e, and \u003cem\u003eCampylobacter\u003c/em\u003e). Cloacal bacterial communities exhibited decreasing diversity and changing composition with turtle age, likely due to shifts in diet as juveniles develop stronger bite force and diving capabilities. Microbial exchange with the environment appears to occur, particularly from turtles to tank water, especially from the carapace. Fungal communities in cloaca and tank water displayed high heterogeneity across individuals, with no age or clinical patterns, possibly due to limited samples and low fungal biomass in cloacal samples. Loggerhead sea turtles host complex microbial communities, including potential bacterial and fungal pathogens, which pose risks to handlers or general public as changing turtle behaviour leads to increased human-turtle interactions. Despite growing research on loggerhead microbiomes, defining a healthy microbiome beyond bacteria remains challenging. Future research should prioritize establishing a description of healthy loggerhead microbiomes at different developmental stages (from eggs and hatchlings to juveniles and adults) to enhance conservation practices and explore potential probiotics and prebiotics for addressing their current and future needs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the Croatian sample collection, we are thankful to Milena Mičić, Karin Gobić Medica and the rest of the staff from the Marine Turtle Rescue Center (Aquarium Pula). For the Italian collection of the samples and recruitment of turtles we are thankful to Pasquale Salvemini of the “Centro di recupero tartarughe marine WWF Molfetta”.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSampling was performed in accordance with the 1975 Declaration of Helsinki, as revised in 2013 and the applicable national laws. The sampling at the Sea Turtle Clinic (Bari, Italy) was conducted with the permission of the Department of Veterinary Medicine Animal Ethic Committee (Authorization # 4/19), while sampling in Croatia was done in accordance with the authorization of the Marine Turtle Rescue Center by the Ministry of Environment and Energy of the Republic of Croatia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSequencing data with non-biological sequences removed is available at EMBL ENA at accessions PRJEB62752, and PRJEB68216 for 16S rRNA gene and PRJEB62762 for ITS2 region sequences. Epizoic samples’ sequencing data obtained from Kanjer et al. [27] and used in this study can be found at ENA under accession PRJEB51458. Complete code and instructions for processing of the sequencing data and subsequent statistical analyses, results, and data visualizations are available at Github (https://github.com/kl-fil/2023-Filek_et_al._TBIOME_project) and ZENODO data depository (doi:10.5281/zenodo.8054926).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work has been fully supported by the Croatian Science Foundation under the project number UIP-2017-05-5635. The work of doctoral student K. Filek has been fully supported by the “Young Researchers’ Career Development Project – Training of Doctoral Students” of the Croatian Science Foundation funded by the European Union from the European Social Fund.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKF and SB concepted and designed the study; AT, MC, AB and SB collected the samples; MŽ, LK and KF carried out the laboratory work; KF and BV conducted the bioinformatics, statistical analyses, and data visualization and interpretation; KF wrote the first draft of the manuscript; all authors revised the paper and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMcFall-Ngai M, Hadfield MG, Bosch TCG, Carey HV, Domazet-Lo\u0026scaron;o T, Douglas AE, Dubilier N, Eberl G, Fukami T, Gilbert SF, Hentschel U, King N, Kjelleberg S, Knoll AH, Kremer N, Mazmanian SK, Metcalf JL, Nealson K, Pierce NE, Rawls JF, Reid A, Ruby EG, Rumpho M, Sanders JG, Tautz D, Wernegreen JJ (2013) Animals in a bacterial world, a new imperative for the life sciences. Proc Natl Acad Sci 110:3229. https://doi.org/10.1073/pnas.1218525110\u003c/li\u003e\n\u003cli\u003eHenry LP, Bruijning M, Forsberg SKG, Ayroles JF (2021) The microbiome extends host evolutionary potential. Nat Commun 12:5141. https://doi.org/10.1038/s41467-021-25315-x\u003c/li\u003e\n\u003cli\u003eRobinson NJ, Pfaller JB (2022) Sea Turtle Epibiosis: Global Patterns and Knowledge Gaps. Front Ecol Evol 10:844021. https://doi.org/10.3389/fevo.2022.844021\u003c/li\u003e\n\u003cli\u003eRobinson NJ, Majewska R, Lazo-Wasem EA, Nel R, Paladino FV, Rojas L, Zardus JD, Pinou T (2016) Epibiotic diatoms are universally present on all sea turtle species. PLoS ONE 11:e0157011\u0026ndash;e0157011. https://doi.org/10.1371/journal.pone.0157011\u003c/li\u003e\n\u003cli\u003eAbdelrhman KFA, Bacci G, Mancusi C, Mengoni A, Serena F, Ugolini A (2016) A First Insight into the Gut Microbiota of the Sea Turtle Caretta caretta. Front Microbiol 7:1\u0026ndash;5. https://doi.org/10.3389/fmicb.2016.01060\u003c/li\u003e\n\u003cli\u003eKuschke SG (2022) What lives on and in the sea turtle? A literature review of sea turtle bacterial microbiota. Anim Microbiome 4:52. https://doi.org/10.1186/s42523-022-00202-y\u003c/li\u003e\n\u003cli\u003eStanford CB, Iverson JB, Rhodin AGJ, Paul van Dijk P, Mittermeier RA, Kuchling G, Berry KH, Bertolero A, Bjorndal KA, Blanck TEG, Buhlmann KA, Burke RL, Congdon JD, Diagne T, Edwards T, Eisemberg CC, Ennen JR, Forero-Medina G, Frankel M, Fritz U, Gallego-Garc\u0026iacute;a N, Georges A, Gibbons JW, Gong S, Goode EV, Shi HT, Hoang H, Hofmeyr MD, Horne BD, Hudson R, Juvik JO, Kiester RA, Koval P, Le M, Lindeman PV, Lovich JE, Luiselli L, McCormack TEM, Meyer GA, P\u0026aacute;ez VP, Platt K, Platt SG, Pritchard PCH, Quinn HR, Roosenburg WM, Seminoff JA, Shaffer HB, Spencer R, Van Dyke JU, Vogt RC, Walde AD (2020) Turtles and Tortoises Are in Trouble. Curr Biol 30:R721\u0026ndash;R735. https://doi.org/10.1016/j.cub.2020.04.088\u003c/li\u003e\n\u003cli\u003eMazaris AD, Schofield G, Gkazinou C, Almpanidou V, Hays GC (2017) Global sea turtle conservation successes. Sci Adv 3:e1600730\u0026ndash;e1600730. https://doi.org/10.1126/sciadv.1600730\u003c/li\u003e\n\u003cli\u003eMazaris AD, Dimitriadis C, Papazekou M, Schofield G, Doxa A, Chatzimentor A, Turkozan O, Katsanevakis S, Lioliou A, Abalo-Morla S, Aksissou M, Arcangeli A, Attard V, El Hili HA, Atzori F, Belda EJ, Ben Nakhla L, Berbash AA, Bjorndal KA, Broderick AC, Cami\u0026ntilde;as JA, Candan O, Cardona L, Cetkovic I, Dakik N, de Lucia GA, Dimitrakopoulos PG, Diryaq S, Favilli C, Fortuna CM, Fuller WJ, Gallon S, Hamza A, Jribi I, Ben Ismail M, Kamarianakis Y, Kaska Y, Korro K, Koutsoubas D, Lauriano G, Lazar B, March D, Marco A, Minotou C, Monsinjon JR, Naguib NM, Palialexis A, Piroli V, Sami K, S\u0026ouml;nmez B, Sourb\u0026egrave;s L, S\u0026ouml;zbilen D, Vandeperre F, Vignes P, Xanthakis M, K\u0026ouml;psel V, Peck MA (2023) Priorities for Mediterranean marine turtle conservation and management in the face of climate change. J Environ Manage 339:117805. https://doi.org/10.1016/j.jenvman.2023.117805\u003c/li\u003e\n\u003cli\u003eHird SM (2017) Evolutionary Biology Needs Wild Microbiomes. Front Microbiol 8:725. https://doi.org/10.3389/fmicb.2017.00725\u003c/li\u003e\n\u003cli\u003eEbani VV (2023) Bacterial Infections in Sea Turtles. Vet Sci 10:333. https://doi.org/10.3390/vetsci10050333\u003c/li\u003e\n\u003cli\u003eDallas JW, Warne RW (2023) Captivity and Animal Microbiomes: Potential Roles of Microbiota for Influencing Animal Conservation. Microb Ecol 85:820\u0026ndash;838. https://doi.org/10.1007/s00248-022-01991-0\u003c/li\u003e\n\u003cli\u003eIUCN (2015) Caretta caretta (Mediterranean subpopulation): Casale, P.: The IUCN Red List of Threatened Species 2015: e.T83644804A83646294\u003c/li\u003e\n\u003cli\u003eBlasi MF, Migliore L, Mattei D, Rotini A, Thaller MC, Alduina R (2020) Antibiotic Resistance of Gram-Negative Bacteria from Wild Captured Loggerhead Sea Turtles. Antibiotics 9:162\u0026ndash;162. https://doi.org/10.3390/antibiotics9040162\u003c/li\u003e\n\u003cli\u003ePace A, Dipineto L, Fioretti A, Hochscheid S (2019) Loggerhead sea turtles as sentinels in the western Mediterranean: antibiotic resistance and environment-related modifications of Gram-negative bacteria. Mar Pollut Bull 149:110575\u0026ndash;110575. https://doi.org/10.1016/j.marpolbul.2019.110575\u003c/li\u003e\n\u003cli\u003ePace A, Rinaldi L, Ianniello D, Borrelli L, Cringoli G, Fioretti A, Hochscheid S, Dipineto L (2019) Gastrointestinal investigation of parasites and Enterobacteriaceae in loggerhead sea turtles from Italian coasts. BMC Vet Res 15:1\u0026ndash;9. https://doi.org/10.1186/s12917-019-2113-4\u003c/li\u003e\n\u003cli\u003eCapri FC, Prazzi E, Casamento G, Gambino D, Cassata G, Alduina R (2023) Correlation Between Microbial Community and Hatching Failure in Loggerhead Sea Turtle Caretta caretta. Microb Ecol. https://doi.org/10.1007/s00248-023-02197-8\u003c/li\u003e\n\u003cli\u003eGleason FH, Allerstorfer M, Lilje O (2020) Newly emerging diseases of marine turtles, especially sea turtle egg fusariosis (SEFT), caused by species in the Fusarium solani complex (FSSC). Mycology 11:184\u0026ndash;194. https://doi.org/10.1080/21501203.2019.1710303\u003c/li\u003e\n\u003cli\u003eTrotta A, Cirilli M, Marinaro M, Bosak S, Diakoudi G, Ciccarelli S, Paci S, Buonavoglia D, Corrente M (2021) Detection of multi-drug resistance and AmpC \u0026beta;-lactamase/extended-spectrum \u0026beta;-lactamase genes in bacterial isolates of loggerhead sea turtles (Caretta caretta) from the Mediterranean Sea. Mar Pollut Bull 164:112015. https://doi.org/10.1016/j.marpolbul.2021.112015\u003c/li\u003e\n\u003cli\u003eTrotta A, Marinaro M, Sposato A, Galgano M, Ciccarelli S, Paci S, Corrente M (2021) Antimicrobial Resistance in Loggerhead Sea Turtles (Caretta caretta): A Comparison between Clinical and Commensal Bacterial Isolates. Animals 11:2435. https://doi.org/10.3390/ani11082435\u003c/li\u003e\n\u003cli\u003eAlduina R, Gambino D, Presentato A, Gentile A, Sucato A, Savoca D, Filippello S, Visconti G, Caracappa G, Vicari D, Arculeo M (2020) Is Caretta Caretta a Carrier of Antibiotic Resistance in the Mediterranean Sea? Antibiotics 9:116\u0026ndash;116. https://doi.org/10.3390/antibiotics9030116\u003c/li\u003e\n\u003cli\u003eGambino D, Persichetti MF, Gentile A, Arculeo M, Visconti G, Curr\u0026ograve; V, Caracappa G, Crucitti D, Piazza A, Mancianti F, Nardoni S, Vicari D, Caracappa S (2020) First data on microflora of loggerhead sea turtle ( Caretta caretta ) nests from the coastlines of Sicily. Biol Open 9:bio045252\u0026ndash;bio045252. https://doi.org/10.1242/bio.045252\u003c/li\u003e\n\u003cli\u003eArizza V, Vecchioni L, Caracappa S, Sciurba G, Berlinghieri F, Gentile A, Persichetti MF, Arculeo M, Alduina R (2019) New insights into the gut microbiome in loggerhead sea turtles Caretta caretta stranded on the Mediterranean coast. Plos One 14:e0220329\u0026ndash;e0220329. https://doi.org/10.1371/journal.pone.0220329\u003c/li\u003e\n\u003cli\u003eBiagi E, D\u0026rsquo;Amico F, Soverini M, Angelini V, Barone M, Turroni S, Rampelli S, Pari S, Brigidi P, Candela M (2019) Faecal bacterial communities from Mediterranean loggerhead sea turtles (Caretta caretta). Environ Microbiol Rep 11:361\u0026ndash;371. https://doi.org/10.1111/1758-2229.12683\u003c/li\u003e\n\u003cli\u003eFilek K, Trotta A, Gračan R, Di Bello A, Corrente M, Bosak S (2021) Characterization of oral and cloacal microbial communities of wild and rehabilitated loggerhead sea turtles (Caretta caretta). Anim Microbiome 3:59. https://doi.org/10/gmptgh\u003c/li\u003e\n\u003cli\u003eBiagi E, Musella M, Palladino G, Angelini V, Pari S, Roncari C, Scicchitano D, Rampelli S, Franzellitti S, Candela M (2021) Impact of Plastic Debris on the Gut Microbiota of Caretta caretta From Northwestern Adriatic Sea. Front Mar Sci 8:637030. https://doi.org/10.3389/fmars.2021.637030\u003c/li\u003e\n\u003cli\u003eScheelings TF, Moore RJ, Van TTH, Klaassen M, Reina RD (2020) The gut bacterial microbiota of sea turtles differs between geographically distinct populations. Endanger Species Res 42:95\u0026ndash;108. https://doi.org/10.3354/esr01042\u003c/li\u003e\n\u003cli\u003eKanjer L, Filek K, Mucko M, Majewska R, Gračan R, Trotta A, Panagopoulou A, Corrente M, Di Bello A, Bosak S (2022) Surface microbiota of Mediterranean loggerhead sea turtles unraveled by 16S and 18S amplicon sequencing. Front Ecol Evol 10:907368. https://doi.org/10.3389/fevo.2022.907368\u003c/li\u003e\n\u003cli\u003eBlasi MF, Rotini A, Bacci T, Targusi M, Ferraro GB, Vecchioni L, Alduina R, Migliore L (2021) On \u003cem\u003eCaretta caretta\u003c/em\u003e \u0026rsquo;s shell: first spatial analysis of micro- and macro-epibionts on the Mediterranean loggerhead sea turtle carapace. Mar Biol Res 17:762\u0026ndash;774. https://doi.org/10.1080/17451000.2021.2016840\u003c/li\u003e\n\u003cli\u003eScheelings TF, Moore RJ, Van TTH, Klaassen M, Reina RD (2020) Microbial symbiosis and coevolution of an entire clade of ancient vertebrates: the gut microbiota of sea turtles and its relationship to their phylogenetic history. Anim Microbiome 2:17\u0026ndash;17. https://doi.org/10.1186/s42523-020-00034-8\u003c/li\u003e\n\u003cli\u003eGuo Y, Chen H, Liu P, Wang F, Li L, Ye M, Zhao W, Chen J (2022) Microbial composition of carapace, feces, and water column in captive juvenile green sea turtles with carapacial ulcers. Front Vet Sci 9:. https://doi.org/10.3389/fvets.2022.1039519\u003c/li\u003e\n\u003cli\u003eTrevelline BK, Fontaine SS, Hartup BK, Kohl KD (2019) Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices. Proc R Soc B Biol Sci 286:20182448. https://doi.org/10.1098/rspb.2018.2448\u003c/li\u003e\n\u003cli\u003eBjorndal KA, Bolten AB, Martins HR (2000) Somatic growth model of juvenile loggerhead sea turtles Caretta caretta: duration of pelagic stage. Mar Ecol Prog Ser 202:265\u0026ndash;272. https://doi.org/10.3354/meps202265\u003c/li\u003e\n\u003cli\u003ePinou T, Domenech F, Majewska R, Pfaller JB, Zardus JD, Robinson NJ (2019) Standardizing Sea Turtle Epibiont Sampling : Outcomes of the Epibiont Workshop at the 37 th International Sea Turtle Symposium. Mar Turt Newsl. https://doi.org/10.13140/RG.2.2.31843.81440\u003c/li\u003e\n\u003cli\u003eKlindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, Gl\u0026ouml;ckner FO (2013) Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res 41:1\u0026ndash;11. https://doi.org/10.1093/nar/gks808\u003c/li\u003e\n\u003cli\u003eWhite TJ, Bruns T, Lee S, Taylor J (1990) AMPLIFICATION AND DIRECT SEQUENCING OF FUNGAL RIBOSOMAL RNA GENES FOR PHYLOGENETICS. In: PCR Protocols. Elsevier, pp 315\u0026ndash;322\u003c/li\u003e\n\u003cli\u003eAndrews S (2010) FastQC: a quality control tool for high throughput sequencing data\u003c/li\u003e\n\u003cli\u003eBolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, Bai Y, Bisanz JE, Bittinger K, Brejnrod A, Brislawn CJ, Brown CT, Callahan BJ, Caraballo-Rodr\u0026iacute;guez AM, Chase J, Cope EK, Da Silva R, Diener C, Dorrestein PC, Douglas GM, Durall DM, Duvallet C, Edwardson CF, Ernst M, Estaki M, Fouquier J, Gauglitz JM, Gibbons SM, Gibson DL, Gonzalez A, Gorlick K, Guo J, Hillmann B, Holmes S, Holste H, Huttenhower C, Huttley GA, Janssen S, Jarmusch AK, Jiang L, Kaehler BD, Kang KB, Keefe CR, Keim P, Kelley ST, Knights D, Koester I, Kosciolek T, Kreps J, Langille MGI, Lee J, Ley R, Liu YX, Loftfield E, Lozupone C, Maher M, Marotz C, Martin BD, McDonald D, McIver LJ, Melnik AV, Metcalf JL, Morgan SC, Morton JT, Naimey AT, Navas-Molina JA, Nothias LF, Orchanian SB, Pearson T, Peoples SL, Petras D, Preuss ML, Pruesse E, Rasmussen LB, Rivers A, Robeson MS, Rosenthal P, Segata N, Shaffer M, Shiffer A, Sinha R, Song SJ, Spear JR, Swafford AD, Thompson LR, Torres PJ, Trinh P, Tripathi A, Turnbaugh PJ, Ul-Hasan S, van der Hooft JJJ, Vargas F, V\u0026aacute;zquez-Baeza Y, Vogtmann E, von Hippel M, Walters W, Wan Y, Wang M, Warren J, Weber KC, Williamson CHD, Willis AD, Xu ZZ, Zaneveld JR, Zhang Y, Zhu Q, Knight R, Caporaso JG (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 37:852\u0026ndash;857. https://doi.org/10.1038/s41587-019-0209-9\u003c/li\u003e\n\u003cli\u003eLozupone C, Lladser ME, Knights D, Stombaugh J, Knight R (2011) UniFrac: An effective distance metric for microbial community comparison. ISME J 5:169\u0026ndash;172. https://doi.org/10.1038/ismej.2010.133\u003c/li\u003e\n\u003cli\u003eGloor GB, Macklaim JM, Pawlowsky-Glahn V, Egozcue JJ (2017) Microbiome datasets are compositional: And this is not optional. Front Microbiol 8:. https://doi.org/10.3389/fmicb.2017.02224\u003c/li\u003e\n\u003cli\u003eMartino C, Morton JT, Marotz CA, Thompson LR, Tripathi A, Knight R, Zengler K (2019) A Novel Sparse Compositional Technique Reveals Microbial Perturbations. mSystems 4:1\u0026ndash;13. https://doi.org/10.1128/mSystems.00016-19\u003c/li\u003e\n\u003cli\u003eOksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O\u0026rsquo;Hara RB, Simpson GL, Solymos P, Stevens MHH, Szoecs E, Wagner H (2020) vegan: Community Ecology Package\u003c/li\u003e\n\u003cli\u003eArbizu PM (2017) pairwiseAdonis: Pairwise Multilevel Comparison using Adonis\u003c/li\u003e\n\u003cli\u003ePeddada S, Lin H (2023) Multi-group Analysis of Compositions of Microbiomes with Covariate Adjustments and Repeated Measures. In Review\u003c/li\u003e\n\u003cli\u003eLin H, Peddada SD (2020) Analysis of compositions of microbiomes with bias correction. Nat Commun 11:3514. https://doi.org/10.1038/s41467-020-17041-7\u003c/li\u003e\n\u003cli\u003eBisanz JE (2018) qiime2R: Importing QIIME2 artifacts and associated data into R sessions\u003c/li\u003e\n\u003cli\u003eWickham H, Averick M, Bryan J, Chang W, McGowan LD, Fran\u0026ccedil;ois R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, M\u0026uuml;ller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019) Welcome to the tidyverse. J Open Source Softw 4:1686. https://doi.org/10.21105/joss.01686\u003c/li\u003e\n\u003cli\u003eWickham, Hadley (2016) ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York\u003c/li\u003e\n\u003cli\u003eReese AT, Dunn RR (2018) Drivers of Microbiome Biodiversity: A Review of General Rules, Feces, and Ignorance. mBio 9:10.1128/mbio.01294-18. https://doi.org/10.1128/mbio.01294-18\u003c/li\u003e\n\u003cli\u003eMariani G, Bellucci F, Cocumelli C, Raso C, Hochscheid S, Roncari C, Nerone E, Recchi S, Di Giacinto F, Olivieri V, Pulsoni S, Matiddi M, Silvestri C, Ferri N, Renzo LD (2023) Dietary Preferences of Loggerhead Sea Turtles (Caretta caretta) in Two Mediterranean Feeding Grounds: Does Prey Selection Change with Habitat Use throughout Their Life Cycle? Anim Open Access J MDPI 13:654. https://doi.org/10.3390/ani13040654\u003c/li\u003e\n\u003cli\u003eCasale P, Abbate G, Freggi D, Conte N, Oliverio M, Argano R (2008) Foraging ecology of loggerhead sea turtles Caretta caretta in the central Mediterranean Sea: evidence for a relaxed life history model. Mar Ecol Prog Ser 372:265\u0026ndash;276. https://doi.org/10.3354/meps07702\u003c/li\u003e\n\u003cli\u003eHao W, Gerdts G, Peplies J, Wichels A (2015) Bacterial communities associated with four ctenophore genera from the German Bight (North Sea). FEMS Microbiol Ecol 91:1\u0026ndash;11. https://doi.org/10.1093/femsec/fiu006\u003c/li\u003e\n\u003cli\u003eMabrok M, Algammal AM, Sivaramasamy E, Hetta HF, Atwah B, Alghamdi S, Fawzy A, Avenda\u0026ntilde;o-Herrera R, Rodkhum C (2023) Tenacibaculosis caused by Tenacibaculum maritimum: Updated knowledge of this marine bacterial fish pathogen. Front Cell Infect Microbiol 12:1068000. https://doi.org/10.3389/fcimb.2022.1068000\u003c/li\u003e\n\u003cli\u003eGilbert MJ, Duim B, Zomer AL, Wagenaar JA (2019) Living in Cold Blood: Arcobacter, Campylobacter, and Helicobacter in Reptiles. Front Microbiol 10:\u003c/li\u003e\n\u003cli\u003eAlbuquerque L, Sim\u0026otilde;es C, Nobre MF, Pino NM, Battista JR, Silva MT, Rainey FA, de Costa MS (2005) Truepera radiovictrix gen. nov., sp. nov., a new radiation resistant species and the proposal of Trueperaceae fam. nov. FEMS Microbiol Lett 247:161\u0026ndash;169. https://doi.org/10.1016/j.femsle.2005.05.002\u003c/li\u003e\n\u003cli\u003eTian Z, Pu H, Cai D, Luo G, Zhao L, Li K, Zou J, Zhao X, Yu M, Wu Y, Yang T, Guo P, Hu X (2022) Characterization of the bacterial microbiota in different gut and oral compartments of splendid japalure (Japalura sensu lato). BMC Vet Res 18:205. https://doi.org/10.1186/s12917-022-03300-w\u003c/li\u003e\n\u003cli\u003eHattenrath-Lehmann TK, Jankowiak J, Koch F, Gobler CJ (2019) Prokaryotic and eukaryotic microbiomes associated with blooms of the ichthyotoxic dinoflagellate Cochlodinium (Margalefidinium) polykrikoides in New York, USA, estuaries. PLOS ONE 14:e0223067. https://doi.org/10.1371/journal.pone.0223067\u003c/li\u003e\n\u003cli\u003eLi S, Young T, Archer S, Lee K, Alfaro AC (2023) Gut microbiome resilience of green-lipped mussels, Perna canaliculus, to starvation. Int Microbiol. https://doi.org/10.1007/s10123-023-00397-3\u003c/li\u003e\n\u003cli\u003eKasana RC, Pandey CB (2018) Exiguobacterium: an overview of a versatile genus with potential in industry and agriculture. Crit Rev Biotechnol 38:141\u0026ndash;156. https://doi.org/10.1080/07388551.2017.1312273\u003c/li\u003e\n\u003cli\u003eLiu F, Li Y, He W, Wang W, Zheng J, Zhang D (2021) Exiguobacterium algae sp. nov. and Exiguobacterium qingdaonense sp. nov., two novel moderately halotolerant bacteria isolated from the coastal algae. Antonie Van Leeuwenhoek 114:1399\u0026ndash;1406. https://doi.org/10.1007/s10482-021-01594-8\u003c/li\u003e\n\u003cli\u003eCong M, Jiang Q, Xu X, Huang L, Su Y, Yan Q (2017) The complete genome sequence of Exiguobacterium arabatum W‐01 reveals potential probiotic functions. MicrobiologyOpen 6:e00496. https://doi.org/10.1002/mbo3.496\u003c/li\u003e\n\u003cli\u003eKeller AG, Apprill A, Lebaron P, Robbins J, Romano TA, Overton E, Rong Y, Yuan R, Pollara S, Whalen KE (2021) Characterizing the culturable surface microbiomes of diverse marine animals. FEMS Microbiol Ecol 97:. https://doi.org/10/gmvjt3\u003c/li\u003e\n\u003cli\u003eFilek K, Lebbe L, Willems A, Chaerle P, Vyverman W, Žižek M, Bosak S (2022) More than just hitchhikers: a survey of bacterial communities associated with diatoms originating from sea turtles. FEMS Microbiol Ecol 98:fiac104. https://doi.org/10.1093/femsec/fiac104\u003c/li\u003e\n\u003cli\u003eLavrinienko A, Scholier T, Bates ST, Miller AN, Watts PC (2021) Defining gut mycobiota for wild animals: a need for caution in assigning authentic resident fungal taxa. Anim Microbiome 3:75. https://doi.org/10.1186/s42523-021-00134-z\u003c/li\u003e\n\u003cli\u003eSalter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, Turner P, Parkhill J, Loman NJ, Walker AW (2014) Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol 12:87. https://doi.org/10.1186/s12915-014-0087-z\u003c/li\u003e\n\u003cli\u003eGrahn N, Olofsson M, Ellnebo-Svedlund K, Monstein H-J, Jonasson J (2003) Identification of mixed bacterial DNA contamination in broad-range PCR amplification of 16S rDNA V1 and V3 variable regions by pyrosequencing of cloned amplicons. FEMS Microbiol Lett 219:87\u0026ndash;91. https://doi.org/10.1016/S0378-1097(02)01190-4\u003c/li\u003e\n\u003cli\u003eJones EBG, Pang K-L, Abdel-Wahab MA, Scholz B, Hyde KD, Boekhout T, Ebel R, Rateb ME, Henderson L, Sakayaroj J, Suetrong S, Dayarathne MC, Kumar V, Raghukumar S, Sridhar KR, Bahkali AHA, Gleason FH, Norphanphoun C (2019) An online resource for marine fungi. Fungal Divers 96:347\u0026ndash;433. https://doi.org/10.1007/s13225-019-00426-5\u003c/li\u003e\n\u003cli\u003eCafarchia C, Paradies R, Figueredo LA, Iatta R, Desantis S, Di Bello AVF, Zizzo N, van Diepeningen AD (2020) Fusarium spp. in Loggerhead Sea Turtles (Caretta caretta): From Colonization to Infection. Vet Pathol 57:139\u0026ndash;146. https://doi.org/10.1177/0300985819880347\u003c/li\u003e\n\u003cli\u003eGeiser DM, Al-Hatmi AMS, Aoki T, Arie T, Balmas V, Barnes I, Bergstrom GC, Bhattacharyya MK, Blomquist CL, Bowden RL, Brankovics B, Brown DW, Burgess LW, Bushley K, Busman M, Cano-Lira JF, Carrillo JD, Chang H-X, Chen C-Y, Chen W, Chilvers M, Chulze S, Coleman JJ, Cuomo CA, de Beer ZW, de Hoog GS, Del Castillo-M\u0026uacute;nera J, Del Ponte EM, Di\u0026eacute;guez-Uribeondo J, Di Pietro A, Edel-Hermann V, Elmer WH, Epstein L, Eskalen A, Esposto MC, Everts KL, Fern\u0026aacute;ndez-Pav\u0026iacute;a SP, da Silva GF, Foroud NA, Fourie G, Frandsen RJN, Freeman S, Freitag M, Frenkel O, Fuller KK, Gagkaeva T, Gardiner DM, Glenn AE, Gold SE, Gordon TR, Gregory NF, Gryzenhout M, Guarro J, Gugino BK, Gutierrez S, Hammond-Kosack KE, Harris LJ, Homa M, Hong C-F, Hornok L, Huang J-W, Ilkit M, Jacobs A, Jacobs K, Jiang C, Jim\u0026eacute;nez-Gasco M del M, Kang S, Kasson MT, Kazan K, Kennell JC, Kim H-S, Kistler HC, Kuldau GA, Kulik T, Kurzai O, Laraba I, Laurence MH, Lee T, Lee Y-W, Lee Y-H, Leslie JF, Liew ECY, Lofton LW, Logrieco AF, S. L\u0026oacute;pez-Berges M, Luque AG, Lys\u0026oslash;e E, Ma L-J, Marra RE, Martin FN, May SR, McCormick SP, McGee C, Meis JF, Migheli Q, Mohamed Nor NMI, Monod M, Moretti A, Mostert D, Mul\u0026egrave; G, Munaut F, Munkvold GP, Nicholson P, Nucci M, O\u0026rsquo;Donnell K, Pasquali M, Pfenning LH, Prigitano A, Proctor RH, Ranque S, Rehner SA, Rep M, Rodr\u0026iacute;guez-Alvarado G, Rose LJ, Roth MG, Ruiz-Rold\u0026aacute;n C, Saleh AA, Salleh B, Sang H, Scandiani MM, Scauflaire J, Schmale DG, Short DPG, \u0026Scaron;i\u0026scaron;ić A, Smith JA, Smyth CW, Son H, Spahr E, Stajich JE, Steenkamp E, Steinberg C, Subramaniam R, Suga H, Summerell BA, Susca A, Swett CL, Toomajian C, Torres-Cruz TJ, Tortorano AM, Urban M, Vaillancourt LJ, Vallad GE, van der Lee TAJ, Vanderpool D, van Diepeningen AD, Vaughan MM, Venter E, Vermeulen M, Verweij PE, Viljoen A, Waalwijk C, Wallace EC, Walther G, Wang J, Ward TJ, Wickes BL, Wiederhold NP, Wingfield MJ, Wood AKM, Xu J-R, Yang X-B, Yli-Mattila T, Yun S-H, Zakaria L, Zhang H, Zhang N, Zhang SX, Zhang X (2021) Phylogenomic Analysis of a 55.1-kb 19-Gene Dataset Resolves a Monophyletic Fusarium that Includes the Fusarium solani Species Complex. Phytopathology\u0026reg; 111:1064\u0026ndash;1079. https://doi.org/10.1094/PHYTO-08-20-0330-LE\u003c/li\u003e\n\u003cli\u003eHoh DZ, Lin Y-F, Liu W-A, Sidique SNM, Tsai IJ (2020) Nest microbiota and pathogen abundance in sea turtle hatcheries. Fungal Ecol 47:100964. https://doi.org/10.1016/j.funeco.2020.100964\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"
[email protected]","identity":"microbial-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meco","sideBox":"Learn more about [Microbial Ecology](https://www.springer.com/journal/248)","snPcode":"248","submissionUrl":"https://submission.nature.com/new-submission/248/3","title":"Microbial Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Caretta caretta, wild microbiome, reptile microbiota, conservation efforts, mycobiota","lastPublishedDoi":"10.21203/rs.3.rs-3893610/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3893610/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe research on microbial communities associated with wild animals provides a valuable reservoir of knowledge that could be used for enhancing their rehabilitation and conservation. The loggerhead sea turtle (\u003cem\u003eCaretta caretta\u003c/em\u003e), a globally distributed species, currently has a thriving population in the Mediterranean Sea, thanks to robust conservation efforts. In our study we aimed to further understand their biology in relation to their associated microorganisms. We investigated epi- and endozoic bacterial and endozoic fungal communities of cloaca, oral mucosa, carapace biofilm samples obtained from 18 juvenile, subadult and adult turtles as well as 8 respective enclosures, during a period of 3 years, by amplicon sequencing of 16S rRNA gene and ITS2 region of nuclear ribosomal gene. Our results reveal a trend of decreasing diversity of distal gut bacterial communities with the age of turtles. Notably, \u003cem\u003eTenacibaculum\u003c/em\u003e species show higher relative abundance in juveniles than in adults. Differential abundances of taxa identified as \u003cem\u003eTenacibaculum\u003c/em\u003e, \u003cem\u003eMoraxellaceae\u003c/em\u003e, \u003cem\u003eCardiobacteriaceae\u003c/em\u003e, and \u003cem\u003eCampylobacter\u003c/em\u003ewere observed in both cloacal and oral samples in addition to having distinct microbial compositions with \u003cem\u003eHalioglobus\u003c/em\u003e taxa present only in oral samples. Fungal communities in loggerheads' cloaca were diverse and varied significantly among individuals, differing from those of tank water. Our findings expand the known microbial diversity repertoire of loggerheads, highlighting interesting taxa specific to individual body sites. This study provides a comprehensive view of the loggerhead sea turtle bacterial microbiota and marks the first report of distal gut fungal communities that contributes to establishing a baseline understanding of loggerhead sea turtle holobiont.\u003c/p\u003e","manuscriptTitle":"Loggerhead Sea Turtles as Hosts of Diverse Bacterial and Fungal Communities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-06 17:01:18","doi":"10.21203/rs.3.rs-3893610/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-03-03T22:56:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-02-19T09:49:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8ca0a804-0808-4488-9d98-445cf59737a7","date":"2024-01-31T07:33:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-25T18:21:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-24T09:45:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-24T09:45:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Microbial Ecology","date":"2024-01-24T09:19:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"
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