Article Images (0)
×![]()
featured_play_listSave article to folder
X
Create new folder
Full Text
PDF
Table of Contents
Abstract
1. Introduction
2. Methods
2.1. Flat Oyster Material And Gross Examination
2.2. Polydorid Molecular Identification And Species Delimitation
2.3. Phylogenetic Analysis
2.4. Prokaryotic Community Associated With Polydora Polychaetes: Metabarcoding Amplicon Sequencing, Taxonomic Annotation And Taxa Composition
3. Results
3.1. Flat Oyster Material And Gross Examination
3.2. Polydorid Molecular Identification And Species Delimitation
3.3. Phylogenetic Analysis
3.4. Prokaryotic Communities Associated With Polydora Polychaetes: Metabarcoding Amplicon Sequencing, Taxonomic Annotation And Taxa Composition
4. Discussion
5. Conclusions
Acknowledgements
Appendix A. Supplementary Data
Abstract
Shell-boring polychaetes belonging to the genus Polydora (Spionidae) infect commercially harvested bivalve molluscs worldwide, reducing their economic value. Due to their limited intraspecific variability, taxonomic identification becomes challenging without molecular approaches. In this study, we identified Polydora hoplura worms infecting flat oysters (Ostrea edulis) in the Gulf of Naples (Italy), providing the first DNA barcode data on the cytochrome c oxidase subunit 1 mitochondrial gene (COI) from its type locality. Three haplotypes with up to ten mutational step differences were detected, suggesting recent introductions from distant populations, including South Africa. The characterization of Polydora associated prokaryotic communities revealed a diverse and fluctuating microbiome linked to these worms, deviating from the usual species-specific pattern observed in other invertebrates. Core and some non-core bacteria could be playing symbiotic roles in nutrient provision, removal of waste products, and antioxidant and detoxifying processes to allow endolithic lifestyle within the borrowed valve chambers. The majority of these microbes though, seem to be acquired horizontally, from an interconnection between the environment and the flat oyster cavity. Indeed, there was a notable detection of opportunistic and potentially pathogenic taxa clusters, including Mycobacterium, Vibrio, Aliiroseovarius and Halarcobacter spp., which in concomitance with the prevalent polydorid infections may prompt implications for the health of the flat oyster host, and for its commercial market, including human consumption. Our study is novel in characterizing bacterial communities associated with shell-boring polychaetes, and sets the bases to propose these parasitic worms as vectors of alterable microbial exchange between oyster hosts and the
Heterogeneous microbiomes associate with shell-boring Polydora hoplura (Polychaeta, Spionidae) affecting the flat oyster Ostrea edulis Laura Núñez-Pons a,b,**, Valerio Mazzella b,c,*, Lucas Pfingsten a, Mario Santoro a,b,** a Department of Integrative Marine Ecology (EMI), Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Naples, Italy b NBFC, National Biodiversity Future Center, Piazza Marina 61, 90133 Palermo, Italy c Department of Integrative Marine Ecology (EMI), Stazione Zoologica Anton Dohrn, Ischia Marine Centre, 80077 Ischia, Naples, Italy A R T I C L E I N F O Keywords: COI gene Polydorid phylogeny Prokaryotic microbiome Mediterranean Sea Allochthonous shell-boring pests Opportunist and pathogen bacterial taxa A B S T R A C T Shell-boring polychaetes belonging to the genus Polydora (Spionidae) infect commercially harvested bivalve molluscs worldwide, reducing their economic value. Due to their limited intraspecific variability, taxonomic identification becomes challenging without molecular approaches. In this study, we identified Polydora hoplura worms infecting flat oysters (Ostrea edulis) in the Gulf of Naples (Italy), providing the first DNA barcode data on the cytochrome c oxidase subunit 1 mitochondrial gene (COI) from its type locality. Three haplotypes with up to ten mutational step differences were detected, suggesting recent introductions from distant populations, including South Africa. The characterization of Polydora associated prokaryotic communities revealed a diverse and fluctuating microbiome linked to these worms, deviating from the usual species-specific pattern observed in other invertebrates. Core and some non-core bacteria could be playing symbiotic roles in nutrient provision, removal of waste products, and antioxidant and detoxifying processes to allow endolithic lifestyle within the borrowed valve chambers. The majority of these microbes though, seem to be acquired horizontally, from an interconnection between the environment and the flat oyster cavity. Indeed, there was a notable detection of opportunistic and potentially pathogenic taxa clusters, including Mycobacterium, Vibrio, Aliiroseovarius and Halarcobacter spp., which in concomitance with the prevalent polydorid infections may prompt implications for the health of the flat oyster host, and for its commercial market, including human consumption. Our study is novel in characterizing bacterial communities associated with shell-boring polychaetes, and sets the bases to propose these parasitic worms as vectors of alterable microbial exchange between oyster hosts and the environment.
1. Introduction
Polydorid (Spionidae) polychaetes comprise a group of taxa with notable ecological and economic relevance in marine ecosystems; either as sediment or biofouling tube dwellers modifying the substrata, or as shell-boring parasites. Morphologically they possess an enlarged fifth chaetiger with modified spines as a major diagnostic trait, functionally used in the specialized burrowing activities (Blake, 1996; Walker, 2011). Within genus Polydora there are several global alien species, in most cases causing shell-boring pests on an array of cultured (in captivity) and commercially harvested (wild) molluscs, including barnacles, oysters, abalone and clams (Çinar, 2013; Simon and Sato-Okoshi, 2015). Interspecific variation is often scarce in polydorids, being diagnostic characters confounding, and making morphological taxonomy poorly resolutive without the combination of molecular approaches (Williams et al., 2017). Indeed, Polydora spp. often exhibit coinciding and overlapping traits, as reported between P. websteri and P. neocaeca (previously referred to as P. haswelli, until updated by Malan et al. (2020)) that hamper morphological discrimination (Blake and Kudenov, 1978; Read, 2010). Furthermore, unlisted historical translocations, frequently related to shipping and farming, combined with intraspecific variability have produced misguided records of alien polydorid pests, as those reported for P. uncinata in Japan (Sato-Okoshi, 1998), now accepted as P. hoplura (Radashevsky and Migotto, 2017; Sato-Okoshi et al., 2017). In other instances, still, allochthonous species have been described as * Corresponding author: Department of Integrative Marine Ecology (EMI), Stazione Zoologica Anton Dohrn, Ischia Marine Centre, 80077 Ischia, Naples, Italy. ** Corresponding authors: Department of Integrative Marine Ecology (EMI), Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Naples, Italy. E-mail address: valerio.mazzella@szn.it (V. Mazzella). Contents lists available at ScienceDirect Aquaculture journal homepage: www.elsevier.com/locate/aquaculture https://doi.org/10.1016/j.aquaculture.2024.741522 Received 19 April 2024; Received in revised form 20 August 2024; Accepted 24 August 2024 Aquaculture 595 (2025) 741522 Available online 26 August 2024 0044-8486/© 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. indigenous, as is the case of P. hoplura in the Mediterranean (Claparède, 1868), or P. websteri in North America (Loosanoff and Engle, 1943), both seemingly originated in Asia, according to recent molecular tracking (Radashevsky and Migotto, 2017; Rice et al., 2018). Nowadays, nonindigenous mollusc-boring pests, as B. proboscidea, P. hoplura, P. neocaeca, and P. cf. websteri, outnumber those of autochthonous origin (e.g., B. pseudonatrix, Dipolydora capensis (Day, 1955)). The specialized endolithic lifestyle of shell borrowing polychaete worms can be compared to that of low oxygen extreme environments, due to the elevated accumulation of anoxic and sulfide-rich detritus (Alayse-Danet et al., 1987; Handley, 1995; Handley and Bergquist, 1997). Still, the microbiomes of these parasites are unstudied, but it is hypothesized that under these conditions, interactions with symbiotic microorganisms may afford mechanisms for detoxification and nutrient recycling (Alayse-Danet et al., 1987; Rieley et al., 1999; Dubilier et al., 2008; Ruehland and Dubilier, 2010). Microbial communities associated with polychaetes are poorly understood, but in general, they reveal high intraspecific variability of environmental origin (Vijayan et al., 2019; Fuirst et al., 2021), in comparison with other holobionts (e.g., corals and sponges) harboring microbiomes strongly structured by host-species (Bourne et al., 2016; Moitinho-Silva et al., 2017; Pita et al., 2018; Dunphy et al., 2019; Dittami et al., 2021). Large microbial permeability with the environment can bring about advantageous, locally adapted microbes (Bourne et al., 2016; Pita et al., 2018; Dittami et al., 2021; Efremova et al., 2024). However, it can introduce opportunistic and pathogenic taxa, favoring microbial imbalances (dysbiosis), and disease states (Corinaldesi et al., 2022). The characterization of microbial communities associated with Polydora pests, on the one hand may unveil symbiotic interactions that facilitate the adaptation to shell-boring habitats, while on the other it may reveal these polychaetes as vectors of pathogens, able to infest edible bivalve populations globally. In the present study we characterized the polydorid worms infecting flat oysters (Ostrea edulis) in the Gulf of Naples (Italy), by integrating morphological and molecular taxonomy approaches. The first molecular data on the COI mitochondrial gene from specimens coming from the type locality is provided, while comparing our samples with other congeneric polydorid species and conspecific representatives from other geographic areas. We further characterized for the first time the associated microbiomes of shell-boring Polydora worms, identifying bacterial groups with diversified potential functionalities for parasitic lifestyle, in relation with mollusc hosts and eventual human consumers.
2. Methods
2.1. Flat oyster material and gross examination
Individuals of flat oyster (n = 12; mean shell length: 9.3 cm, ranging from 7.7 to 10.5 cm) farmed in suspended lantern nets at ~2–3 m from the sea surface and ~ 10 m from the bottom, were obtained on February 18, 2019 from an experimental oyster farm from off Castel Volturno coastline (Caserta, Campania), on the Tyrrhenian Sea (Italy). The flat oysters were refrigerated (+4◦) and transported to the laboratory for dissection within 24 h after sampling. Before dissection, occurrence, shape, and location of polydorid burrows in the shell were established using X-rays (Diez et al., 2013). Then, flat oysters were opened individually, and the left and right valves of individuals were observed under an Axio Zoom V16 stereomicroscope (Zeiss) to typify damage due to polydorid polychaetes. The classification scheme to determine the degree of infestation followed Martial et al. (1996) criteria based on gross examinations of the inner surface of valves. In brief, this scheme included the levels: class 1: presence of worm, burrows visible; class 2: fewer than two chambers and less than 10 % of the shell surface infested; class 3: more than two chambers or 10–25 % of surface infested; and class 4: >25 % surface infested. To collect the polydorid polychaetes, flat oysters were dissected under sterile conditions, and valves were placed in sterile petri dishes and broken up with a hammer, following the marks of the borrowed galleries. The worms were then extracted with tweezers under an Axio Zoom V16 stereo-microscope and identified using an Axioskop 2 plus optical microscope (Zeiss), following the descriptions of Radashevsky and Migotto (2017) and Sato-Okoshi et al. (2017). The infestation rate was calculated by the number of worms per flat oyster, and the prevalence as the percentage of infected flat oysters. Worm samples for morphological identification were preserved in 70 % ethanol, while worm material for molecular identification and microbiome characterization were rinsed 3 times with sterile seawater and kept at − 80 ◦C until processed (see below).
2.2. Polydorid molecular identification and species delimitation
DNA from eight frozen polydorid worms was extracted using QIAGEN PowerSoil®Pro Kit (QIAGEN GmbH, Hilden, Germany), and with Quick-gDNA Miniprep Kit (ZYMO RESEARCH, California, USA) for another five samples, following manufacturer’s instructions. DNA yields were estimated through Thermo Scientific NanoDrop® TM 1000. Three primer pairs (18S-1F1/18S-1R632, 18S-2F576/18S-2R1209 and 18S3F1129/18S-R1772) (Puillandre et al., 2021) were used to amplify the nuclear 18S rRNA gene (~1772 bp fragment), while the COI gene (~ 680 bp fragment) was amplified with primers Dorid COI⋅3F and Dorid COI.1R (Williams et al., 2017) (Table S1). We performed PCR reactions in 25 μL containing: 2.5 μL (2 mM) of Buffer, 1 μL dNTPs (2 mM), 0.8 μL (20 μg/μL) of BSA, 0.3 μL (5 U/μL) of Promega Taq DNA Polymerase, 0.8 μL (10 mM) of each primer, and 1 μL DNA template. Thermocycling conditions were: denaturation at 95 ◦C for 5 min, 35 cycles at 94 ◦C for 50 s, 60 ◦C (18S) or 45–50 ◦C (COI) for 50 s and 72 ◦C for 90 s, with a final extension of 72 ◦C for 10 min. PCR products were checked in 1 % agarose gels under UV light, cleaned from primers and impurities using AMPure® XP beads (Beckman Coulter, Inc.), and quantified on NanoDrop®. Purified PCR products were sequenced at Stazione Zoologica Anton Dohrn, Molecular Biology Service (RIMAR Deptartment) with a Thermo Fisher Scientific 48 capillary ABI 3730xl DNA Analyzer, using 4.5 micromolar of the corresponding PCR primer pair, and 15 femtomoles/uL of DNA template. Forward and reverse complementary sequences and contigs were assembled, corrected, and checked for stop codons using the translate function (DNA to protein) in Geneious Prime® 2022.2.2 (http://www.geneious.com). Taxonomy identification was checked by BLAST against NCBI GenBank (Altschul, 1997). All sequences generated in the present study were deposited in the GenBank nucleotide sequence database under the accession numbers OQ626355–OQ626367 (Table S2). Species delimitation was calculated on COI data, comparing intraspecific P. hoplura dissimilarities against the closest congeneric species, P. aura, and applying three methods via web servers. Automatic Barcode Gap Discovery (ABGD) (www.abi.snv.jussieu.fr/public/abgd/) calculates the barcode gap by setting a series of prior intraspecific divergences, which are iteratively refined. In the settings Kimura-2 parameter (K2P) and relative gap width (X = 1.5) were selected (Puillandre et al., 2021). Assemble Species by Automatic Partitioning (ASAP) (https://bioinfo. mnhn.fr/abi/public/asap/asapweb.html) computes species partitions ranked by score, based on pairwise genetic distances, probability of panmixia (p-val), and relative gap width (W). It was run with Kimura (K80) ts/tv set to 2, and number of species predicted by ASAP 1st and 2nd scores were selected (Puillandre et al., 2021). Bayesian implementation of the Poisson-Tree-Processes model (bPTP) (https://species.h-its.org/ptp/) infers speciation events using MCMC based on a shift in the number of substitutions between internal nodes. It was fed the IQTree ML tree, set for 50 million generations, with 100 generations sampling frequency and 25 % burn-in (Zhang et al., 2013).
2.3. Phylogenetic analysis
The resulting COI gene sequences were used for phylogenetic analyses and species delimitation, against sequences from polychaetes in genus Polydora, along with the outgroup Pseudopolydora dayii Simon, 2009 (KV6778681) in family Spionidae, as in Martinelli et al. (2020). All reference data were downloaded from Genbank (Table S3), and aligned against our sequences with MAFFT (Katoh and Standley, 2013) under default settings in Geneious Prime® 2022.2.2 (Kearse et al., 2012). The alignments were consensually trimmed to 606 base pairs (bp) long, and missing data was filled in with Ns in reference sequences, and in samples Pol-03B and Pol–010B. Maximum likelyhood (ML) trees were built on IQTree with 1500 ultrafast bootstrap replicates (Nguyen et al., 2014), under the most accurate genetic model: GTR + F + I + G4 (Kalyaanamoorthy et al., 2017). Bayesian inference (BI) trees were constructed on MrBayes (Ronquist et al., 2012) with the GTR GAMMA model and Markov Chain Monte Carlo (MCMC) set for 1,100,000 generations, 4 chains, 200 generations sampling frequency, and 500 burn-in values (Table S3). Phylogeny analytic tools were run on CIPRES (http://www.phylo.org/) (Miller et al., 2010), ML and BI trees were visualized on Figtree (http://tree.bio.ed.ac. uk/software/figtree/), and final trees were built on R-Studio version 2022.12.0 + 353 (RStudio Team, 2020) run with R version 4.2.2 (R Core Team, 2022) R A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. - References - Scientific Research Publishing, n.d.), using package ggtree (Yu et al., 2017).
2.4. Prokaryotic community associated with Polydora polychaetes: Metabarcoding amplicon sequencing, taxonomic annotation and taxa composition
DNA aliquots (~25 μL) from the eight polydorids extracted with QIAGEN PowerSoil®Pro Kit (see above) were sent to Station Biologique de Roscoff (Platform Genomer; SBR France) for library preparations and sequencing. Amplification of the hypervariable region 16S rRNA gene V3-V4 locus (Escherichia coli position: 341–805) was performed following the 16S Metagenomic Sequencing Library Preparation protocol (Illumina Inc., 2013; Wasimuddin et al., 2020; Fadeev et al., 2021), using Bakt_341F primer 5’TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG[CCTACGGGNGGCWGCAGGTCTCGTGG]3′ and Bakt_805R primer 5’GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG- [GACTACHVGG GTATCTAATCC] 3′, which integrated the Illumina adapters (Klindworth et al., 2013). PCR mix was prepared using the Q5® High-Fidelity PCR Kit (New England BioLabs, MA, USA), with metagenomic DNA (5 ng/μL) 2.5 μL, forward primer (1 μM) 5 μL, reverse primer (1 μM) 5, for a total volume of reaction of 25 μL, and the Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA, USA). Reactions were performed in a 96-Well Thermal Cycler following thermocycling conditions of: 95 ◦C for 3 min followed by 25 cycles of 95 ◦C for 30 s, 55 ◦C for 30 s and 72 ◦C for 30 s and a final elongation performed at 72 ◦C for 5 min and a 4 ◦C hold. PCR products were purified with the AMPure XP beads (Beckman Coulter, Brea, CA, USA) to eliminate free primers and primer–dimer species. Quantifluor® ds DNA System (Promega, WI, USA) was used to quantify libraries, and mean fragment size was determined using a LabChip® GX Touch™ (Perkin Elmer, MA, USA). All samples were then pooled at equimolar concentration of 4 nM, diluted to 4 pM, spiked with 10 % PhiX (Illumina) and sequenced on an Illumina MiSeq sequencer using a MiSeq v3 kit (2x300bp, paired-end, 600-cycle) targeting ~ 400–450 bp amplification products. Sequencing data for 16S rRNA gene and associated metadata are available at National Center for Biotechnology Information (NCBI, Genbank) under BioProject PRJNA1067543, while other data will be made available by contacting the corresponding author. Demultiplexed fastq files from polydorid samples (once excluded blanks and PCR negatives) were imported into QIIME2 v.2021.11 (Bolyen et al., 2019). Raw sequencing reads (280–444 bp) were submitted to DADA2 (Callahan et al., 2016) with left and right truncation options set at 260 and 180 bp, and other parameters left as default. Denoising steps, removed chimeric sequences and singletons and joined denoised paired-end reads into high-quality Amplicon Sequencing Variants (ASVs) (Table S4). Taxonomy was assigned against the 16S SILVA v.138_1 reference database (Quast et al., 2013), which was pre-trained using qiime2 RESCRIPt (REference Sequence annotation and CuRatIon Pipeline) for formatting, managing, manipulating and evaluating sequence reference databases (Robeson et al., 2021). The ASV table was filtered from features with lower total reads than 10, and from non-targeted DNA, such as “Chloroplast” and “Mitochondria”. Alpha-rarefaction plots (q2-diversity) confirmed that amplification was sufficient to reach a plateau, in which diversity would not increase with deeper sequencing (Table S5; Fig. S1). A rarefaction of 7000 guaranteed a full coverage of bacterial/ archaeal diversity, retaining all the samples. Feature ASVs counts, taxonomy annotations and metadata tables were imported into R version 4.2.2 (2022− 10− 31) for downstream analyses. Taxa community composition examinations and core microbiome analyses (at 100–50 % of prevalence) were performed on unrarefied data to define shared core ASVs. The Qiime2R package was used to import qiime2 artifacts into the R environment (https://github. com/jbisanz/qiime2R). Further packages used for data manipulation, diversity and composition inspections, other downstream explorations and plotting visualization for taxa bar plots and heatmaps were phyloseq (McMurdie and Holmes, 2013), vegan (Oksanen, 2024), microbiome (Leo and Shetty, 2017), Phylosmith (Smith, 2019), microViz (Barnett et al., 2021) and ggplot2 (Wickham, 2016). The heterogeneity of the prokaryotic community structure across Polydora hosts was compared with other microbial data sets coming from marine model holobionts with functional symbiotic microbiomes: scleractinian corals (Pocillopora acuta) and demosponges (Chondrilla nucula) (Núñez-Pons et al., 2023; Mazzella et al., 2024). Beta dispersion (R betadisper (Anderson, 2006)), based on Aitchison distance matrices (Aitchison, 1982) was applied to measure the average dissimilarity from individual observation units (ASVs) to their group centroid in multivariate space (999 permutations and significance set to q-values <0.05; i.e., false discovery rate adjusted p-value). Then, ANOVA and post hoc Tukey’s tests were performed to determine if the dispersions (variances) of groups were different (p-value<0.05).
3. Results
3.1. Flat oyster material and gross examination
The prevalence of infestation in flat oysters was 100 %, although the degree of shell damage was class 2 in 2 flat oysters, class 3 in 4 flat oysters, and class 4 in 6 flat oysters. Polydorids excavated U-shaped burrows in the shells with gross damages, characterized by mud blisters and abnormal black organic and/or calcareous deposits on the inner surface of the valves, deriving in abnormal shell formation. Underneath these macroscopic alterations, after removal of the superficial calcareous layers, boring galleries from the polychaetes could be observed, harboring the living polydorid worms in variable number. The galleries were labyrinthine, with mud accumulations, and accompanied by sulfide to putrid odors (Fig. 1). In general, each oyster harbored from one to three worms (Table 1). We were able to extract 13 intact worms, five used for morphological and molecular taxonomy and feature observations, and eight used for microbiome characterization and DNA barcoding (see below; Fig. 1; Table S2). Specimens examined in this study agree with the previous redescription of P. hoplura (Radashevsky and Migotto, 2017; SatoOkoshi et al., 2017). In particular, worms were morphologically identified as P. hoplura based on the occurrence of the fifth modified setiger, the presence of heavy recurved spines in the posterior notopodia, occipital antenna on the caruncle, and the caruncle extending nearly to the end of the chaetiger 3. Mature females with oocytes in the coelom and egg capsules in their burrows were commonly observed, as well as their larval stages.
3.2. Polydorid molecular identification and species delimitation
The 18S barcode (1787 bp) obtained from three individuals displayed >99 % blast match with several Polydora species (e.g., P. websteri, P. hoplura, P. haswelli, P. spongicola, P. calcarean, P. brevipalpa, P. onagawaensis, P. lingshuiensis, and Polydora sp.). The CO1 fragment spanning 583–654 bp was retrieved from 13 worms. Eight of these sequences reported 100 % match, one sequence was 99 % equal, and the remaining four sequences had 98.5 % identity with a sequence of P. hoplura from South Africa (KY677865), confirming the morphological classification. Within our COI barcodes, sequences from samples Pol-07 A (633 bp), Pol-07B (633 bp), Pol-010C (654 bp), Pol-012 A (659 bp) differed by 11 nucleotide calls from Pol-01 (620 bp), and by 10 calls from Pol-02 A (645 bp), Pol-03 A (634 bp), Pol-03B (583 bp), Pol-04 A (623 bp), Pol07C (639 bp), Pol-09 (621 bp), Pol-010 A (631 bp) Pol-010B (594 bp), and from the most matching reference barcode –P. hoplura from South Africa (KY677865). Pol-01 only varied in one base call from this last group of samples and the closest reference (Table 1). The present 13 query COI sequences were clustered into two partitions according to ASAP: Group 1 including Pol-01, Pol-02 A, Pol-03 A, Pol–03B, Pol-04 A, Pol–07C, Pol-09, Pol-010 A and Pol–10B; and specimens Pol-07 A, Pol–07B, Pol-010C and Pol-12 A forming Group 2 (ASAP: P-val (rank) = 1.86e-01; Threshold dist = 0.012). ABGD instead discriminated three groups, further separating Pol-01 as a single partition (ABGD: P = 1.29e-02, Barcode gap distance = 0.034). When including other reference P. hoplura data, both ASAP and AGBD models yielded two partitions, one group formed by our barcodes and two South African P. hoplura sequences, and another group comprising other P. hoplura from South Africa (ABGD: P = 1.00e-01, Barcode gap distance = 0.128; ASAP: P-val (rank) = 1.00e-01; Threshold dist = 0.031). Finally, intrageneric comparisons with the closest congeneric species, P. aura, revealed a clear separation into two clusters: one formed by all the P. hoplura sequences (ours and reference data), and another by those corresponding to P. aura (ABGD: P = 3.59e-02, Barcode gap distance = 0.107; ASAP: P-val (rank) = 1.70e-01; Threshold dist = 0.099). bTPT also supported these two major intrageneric, interspecific groups. It is L. N úñez-Pons et al. Aquaculture 595 (2025) 741522 5 highly probable that the intraspecific sub-partitions are not taxonomically significant, due to the low barcode gab and threshold distance values reported, below Hebert et al. (2004) species delimitation threshold established at 0.05 (Tables 1 and S3).
3.3. Phylogenetic analysis
COI phylogenetic ML and BI trees had identical topologies. Polydora hoplura sequences branched together in a monophyletic clade with high support (93 % ML bootstrap value and 0.99 pp posterior probability) separated from other representative Polydora. Other congeneric taxa clustered together accordingly by species, and included: P. aura as the most related species, followed by P. websteri, P. lingshuiensis, P. cornuta and P. brevipalpa, and P. neocaeca and P. nuchalis yielding other minor sub-divisions. Within the P. hoplura clade there were two principal subpartitions, dividing our Italian sequences together with a South African reference barcode, from other P. hoplura from South Africa and South Korea. These last South Korean barcodes were submitted originally as Polydora sp. in GenBank, but were later updated to P. hoplura by Lee et al. (2020). Similarly, as the other Korean Polydora sp., that were redefined as P. haswelli (Lee et al., 2020), and are now accepted as P. neocaeca according to Malan et al. (2020). The observed P. hoplura internal branching indicates polyphyletic associations in specimens sampled up to date from all these areas. Our samples were further subdivided in minor sub-groups, corroborating the outcomes from the genetic distance approaches, and low reflectiveness of geographic collection sites, even if sampling could not be considered exhaustive (Figs. 2, S2, Table S3).
3.4. Prokaryotic communities associated with Polydora polychaetes: Metabarcoding amplicon sequencing, taxonomic annotation and taxa composition
A total of 701 different ASVs were distributed in 8 samples, with a frequency ranging 7029–80652 per sample (Table S4). The prokaryotic communities within the polychaete hosts included Bacteria and Archaea, represented in 25 phyla, 44 classes, 99 orders, 140 families and 237 genera. Around 48 % of the sequences were annotated at the genus level, whereas only 30 ASVs (4 %) had species level annotation (Suppl. Table S6). Top phyla were Proteobacteria (48 %), Actinobacteriota (24 %), Bacteroidota (17 %) and Planctomycetota (3 %); with Alphaproteobacteria (30 %), Actinobacteria (19 %), Gammaproteobacteria (18 %), Bacteroidia (17 %) and Acidimicrobiia (5 %) being the most abundant classes; and Rhodobacterales (22 %), Flavobacteriales (14 %) and Corynebacteriales (13 %) the most represented orders. The most abundant families were Rhodobacteraceae (22 %), Mycobacteriaceae (12 %), Flavobacteriaceae (12 %) (Fig. 3). While the most represented genus was Mycobacterium (12 %), followed by Aliiroseovarius (3 %), and Ilumatobacter, Ruegeria, Pseudahrensia, Nocardioides, Arenicella, Cutibacterium, Vibrio, Phaeobacter and Halarcobacter (all these accounting for 2 % relative abundance; Fig. S3). The diversity, in terms of richness ranged from 23 observed ASVs in Pol-012 A to 532 ASVs in Pol–03B, and Shannon indexes ranging from 2 to 5.4 respectively in these same samples; whereas the lowest Pielou evenness value was recorded in Pol-07B (0.5) and the highest in Pol-09 (0.85). More than 50 % of the total relative abundance was occupied by dominant core ASVs (referred to as those that exceed 0.2 % detection level in over 50 % of the samples) in three specimens: Pol-012 A (71 %), Pol-07B (61 %), and Pol-01 (50 %). Certain prokaryotic communities were dominated > 60 % by a single microbial strain, as in Pol-012 A, with predominance of a microbe in genus Ralstonia, and in Pol-07B dominated by a Mycobacterium. The same Mycobacterium strain was dominant in sample Pol–010B, while in Pol-01 a Cutibacterium microorganism was the leading taxon. In these last two cases, these major ASVs were > 30 % in community proportion (Table 2). Three microbes in genera Ralstonia, Algibacter, and Cutibacterium were found to be core taxa –shared across all eight polychaete hosts (100 % prevalence); and the core size, as the percentage relative abundance covered by these core taxa, was larger in samples Pol-012 A, Pol-01 and Pol-07 A (58–12 %) with respect to the other five samples (3.7–0.1 %). At a lower level of prevalence across samples, 40, 13 and seven taxa were shared within four, five and six specimens respectively (50 %, 65 % and 75 % prevalence). These shared taxa will be discussed in the sections below (Figs. 4, S4). Beta dispersion analysis incorporating external microbial datasets demonstrated that P. hoplura had the most dispersive and heterogeneous microbial communities, revealing the largest distances to the centroid (58.33; ANOVA p-value = 5.158e-10), as compared to corals (35.75; Tukey p-value = 9.30e-06) or sponges (15.77; Tukey p-value = 0.00e+00) (Figs. 5 and S5; Table S7).
4. Discussion
All specimens of flat oyster coming from Castel Volturno were infected with P. hoplura worms, and exhibited diverse levels of severity of infection. Flat oysters were visibly affected by gross pathological changes in their internal valves, in particular with conspicuous black spots, and blisters containing organic and/or calcareous deposits. Such signs reflect mollusc hosts responses to withstand polydorid excavating activities, and repair the shell structural material and nacre layers after worms’ penetration (Haigler, 1969; Blake and Evans, 1973). Thus, even though polydorid infestations may be intricate to recognize by consumers (unawareness, meat is excised from original infected valves), this energy costly regeneration process drives to slower growth and reproduction rates, and the development of watery and less appealing meat in infected oysters with respect to non-infected counterparts. Consequently, the commercial value of parasitized oyster batches is significantly in decline (Handley, 1998; Royer et al., 2006; Chambon et al., 2007). Polydora hoplura is one of the largest species among its congeners (reaching 6 cm length), and one of the most destructive shell-boring pests for oyster and abalone aquaculture industries (Sato-Okoshi et al., 2017, 2023). Originally described in the Gulf of Naples (Tyrrhenian Sea), P. hoplura is now documented from all continents except the polar regions (Radashevsky et al., 2023). This global distribution is hypothesized to be the result of continuous accidental transportation via vessel hull fouling and aquaculture means, and consequent hosts translocation and transplantation (Simon and Sato-Okoshi, 2015; Radashevsky and Migotto, 2017). Although P. hoplura shows a ubiquitous distribution in the Mediterranean basin, affecting several bivalve species (Radashevsky and Migotto, 2017), only recently Radashevsky et al. (2023) reported molecular data from this area. In this latter study using specimens of P. hoplura from different areas, nuclear 18S, 28S makers were poorly informative within polydorids, whereas histone 3 and in particular mitochondrial 16S were much more variable for species delimitation (Radashevsky et al., 2023). In particular, the 18S and 28S markers alone are not discriminative for species identification within genus Polydora (Ye et al., 2019; Lee et al., 2020; Martinelli et al., 2020; Sato-Okoshi et al., 2023). In the present study we increase this knowledge providing phylogenetic inferences of Polydora spp. based on the first mitochondrial COI barcodes from the type locality and those available in GenBank. In our study, the mitochondrial COI unequivocally identified all specimens in the present survey as P. hoplura. Three haplotypes differing by one, ten or eleven base substitutions were found among 13 COI sequences. One haplotype comprising four barcodes and another represented by only one sequence, were unique. In lieu, the remaining haplotype (eight sequences) was identical to a reference haplotype from a distant coastal area of South Africa. COI phylogeny corroborated these findings, placing our three haplotypes (internal branches) within the same monophyletic entity as other geographic populations of P. hoplura from South Africa and South Korea, with high bootstrap and posterior probability support. The conspecificity of the specimens under study was also confirmed by genetic distance analyses, revealing threshold distances across the three haplotypes lower (1 to 3.5 %) than the 5 % species delimitation threshold established by Hebert et al. (2004). Also, the intraspecific genetic distances among P. hoplura from other areas respected this threshold, with South Korean and South African clades being in average more closely related with each other (0.8 %), than with the Italian haplotypes (4.2 and 4.7 % respectively), except for the South African shared haplotype mentioned above. Instead, interspecific genetic distances between our specimens and the closest Polydora representative, P. aura, were 18 %. Similar results were obtained by Malan et al. (2020), who found interspecific dissimilarities between P. neocaeca and P. hoplura based on COI ranging between 18.02 % and 19.42 %, and intraspecific variability in individuals of P. neocaeca from distant localities ranging between 0.1 % and 4.8 % (Malan et al., 2020). As shellboring pests infesting commercial fishing products, polydorid species exhibit widespread distributions, due to aquaculture and/or shipping activities, covering international ranges. Molecular investigation is very useful to reconstruct historical translocation events, and decipher the original locality of these parasites (Radashevsky and Migotto, 2017; Rice et al., 2018; Radashevsky et al., 2023). Since the first documentation in the Tyrrhenian Sea (Claparède, 1868), P. hoplura has been recorded widespread, including other areas in the Mediterranean (Ionian), Atlantic (Spain, France), Pacific (South Korea, Australia, Japan, USA), Indic (South Africa) (Radashevsky and Migotto, 2017; Radashevsky et al., 2023), and was eventually recognized as an alien species from its type locality (Sato-Okoshi et al., 2017). Clades from Italy and South Korea were found to be more homogeneous (lower intra clade distances 0.8 and 0 % respectively), than those from South Africa (1.8 %). Larger genetic diversities have been already recognized in South African Table 2 Microbial community exploration. Diversity and structural indexes of prokaryotic communities associated to Polydora hoplura polychaetes at the ASV (amplicon sequence variant) level. Sample Observed (ASV) Shannon Pielou evenness Core proportion** Low abundance Rare abundance† Pol-01 74 3.423249 0.7953526 0.5035388 0.007319581 0.09194846 Pol-03B 532 5.426867 0.864613 0.1514792 0.322355225 0.37483922 Pol-04 A 140 3.742273 0.7572934 0.1539945 0.067033976 0.20030609 Pol-07 A 146 3.962853 0.7951778 0.410047 0.075650284 0.23259483 Pol-07B 124 2.396696 0.4972107 0.6146515 0.085929432 0.07652754 Pol-09 320 4.909522 0.8511181 0.2269263 0.199759586 0.29763193 Pol-010B 492 4.25648 0.6866976 0.3332713 0.18207856 0.19250608 Pol-012 A 23 2.022704 0.6450988 0.7073552 0 0.0529236 * The dominance core index gives the (core) relative proportion of the core species that exceed detection level 0.2 % in over 50 % of the samples. † The rarity index characterizes the concentration of species at low and rare abundance in that sample. Fig. 4. Compositional heatmap of centered log ratio (CLR). Values of the 40 prokaryotic ASVs shared across at least 50 % of the samples in Polydora hoplura hosts infesting Ostrea edulis flat oysters. Core size pies for each individual worm are depicted below the heatmap, showing the proportion occupied by the core microbiome (represented by the three taxa shared across 100 % of the samples) with respect to the total microbiome. Core taxa is coded in black, while non-core variable microbiomes are coloured matching each individual Polydora host. Core sizes varied from 0.58 % in Pol-012 A to 0.001 % in Pol–010B. Taxonomy is provided at the best annotation available. P. hoplura populations, leading to recall this region as the species’ natural range (David et al., 2016; Williams et al., 2017). However, there are points of hesitation in declaring South Africa the original locality, as the haplotypes’ concentration here likely reflects >75 years of anthropogenic introductions from genetically distinct source populations. At the moment, the true provenance of P. hoplura is hypothesized in the Indo–West Pacific or Northwest Pacific (Radashevsky and Migotto, 2017; Radashevsky et al., 2023). A common indicator of artificially translocated species is the existence of two or more coincident haplotypes among multiple distant geographical populations (Simon, 2009; Sato-Okoshi et al., 2017; Rice et al., 2018; Radashevsky et al., 2019). On what regards the Mediterranean basin, recent translocations may be reflected in the haplotype sharing between Italian (Malan et al., 2020) (Tyrrhenian and Ionic) 16S barcodes and identical entries from Atlantic (France and Spain) and Pacific (Japan) specimens (Radashevsky et al., 2023), and now in some of our sequences coinciding with South African references. In their comprehensive survey using the 16S maker Radashevsky et al. (2023), did not reveal any closeness among Mediterranean and South African barcodes, but also the genetic variability reported was reduced to a single Mediterranean haplotype. Instead, based on the COI we retrieved three haplotypes only from the Gulf of Naples, at times differing by more than ten mutational steps from one another. Fact that could indicate introductions from distant populations, as observed in geographically separated haplotypes of P. neocaeca recording more than 19 mutational steps (Malan et al., 2020). All this suggests, on the one hand, that both 16S and COI seem suitable markers for polydorids, yet curated confrontation may reveal different performances in the diverse fields of application. And on the other hand, that we still dispose of a too small coverage of global haplotypes diversity. Therefore, more geographic molecular data is needed to be gathered in order to repopulate databases, and be able to reconstruct the natural distribution ranges and translocation routes of these widespread shell-boring parasites. A major novelty was the characterization of the prokaryotic communities associated with shell-boring polychaetes. Three core bacterial ASVs were shared across all the Polydora worms. The first member belonged to genus Cutibacterium (Actinomycetota), which include human skin-associated commensals, in particular C. acnes, which is causative of infection processes, such as acne vulgaris (Mayslich et al., 2021). In the marine environment though, C. acnes are core microbes and nutrient provisioning symbionts in Capitella teleta polychaetes (Jang et al., 2022). It is plausible a seeming partnership between Cutibacterium and P. hoplura. An Algibacter sp. (Bacteroidota) was the second core associate, with congeneric strains being often described in molluscs (Yin et al., 2021), echinoderms (Nedashkovskaya et al., 2007) and algal microbiomes (Nedashkovskaya et al., 2004). The third core taxon was a Ralstonia Proteobacterium. The genus comprises terrestrial phytopathogens R. solanacearum (Genin and Denny, 2012), and human clinical strains (Coenye et al., 2003). In the marine realm, Ralstonia spp. assist ascidians and anemones in vanadium sequestration (Schuett et al., 2007; Romaidi, 2016; Ueki et al., 2019). The metal detoxifying capabilities of these bacteria were also proposed to aid sipunculid hosts (Li et al., 2023); whereas their association with oligochaete worms Tubificoides benedii, was more linked to their sulfur metabolism, as reported in deepsea hydrothermal vent ectosymbionts (Ruehland and Dubilier, 2010). Ralstonia spp. are chemolithoautotrophs exhibiting mixotrophic strategies (Raberg et al., 2018), including Sammox: thiosulfate reduction coupled with anaerobic ammonium oxidation, with generation of sulfide (Li et al., 2020). This last aspect could be correlated with the hydrogen sulfide accumulation within the chambers borrowed by P. hoplura (Handley, 1995; Handley and Bergquist, 1997). Non-core bacteria incorporated symbiotic-beneficial to transientopportunistic commensals. P. hoplura were found to possess potentially beneficial Phaeobacter and Ruegeria microbes, which together with Pseudovibrio spp. are known as antagonistic agents against other bacteria, due to the production of antibiotic tropodithietic acid (Porsby et al., 2008; Gram et al., 2010). In particular, Phaeobacter spp. has demonstrated efficient inhibition against fish and mollusc pathogens in aquaculture conditions (Rao et al., 2007; Porsby et al., 2008; D’Alvise et al., 2013) (cited in Thole et al., 2012). Similarly, Nocardioides spp. detected in some samples, have proved antimicrobial properties, and capability to emit toxic organic compounds from isolates in bivalves from the Suez Canal (El-Shatoury, 2007). Pseudahrensia spp. (phylum Pseudomonadota), described in Japanese flying squids (Kim et al., 2016), and comprising free living strains (Jung et al., 2012) could represent innocuous associates in Polydora. Whereas Arenicella spp. have reported relationship with incipient necrotic cuticles in American and European lobsters (Whitten et al., 2014). Other bacterial groups in lieu, could be metabolically complementary within the polydorid host. Halarcobacter (syn. Proposed Arcobacter) can be linked to detrimental strains from scleractinian corals with black band disease in Netherlands Antilles (Frias-Lopez et al., 2002); or those in enteric disorders in children (Vandamme et al., 1992; Wassenaar and Newell, 2006). But, marine Arcobacter further include chemolithoheterotrophic species with denitrification and sulfide oxidation coupling, which could be involved in nitrogen excretion under sulfide-rich conditions like those in polidorid mud blisters (Callbeck et al., 2019). Ilumatobacter spp. instead, recorded in tube-forming polychaetes (Fuirst et al., 2021), sipunculid worms (Li et al., 2023), and sponges (Fujinami et al., 2013), are carbon monoxide detoxifiers (Fusi et al., 2023). They constitute efficient agents against oxidative stress (Fusi et al., 2023), a vital property for polychaetes living under extreme environments, including shell-boring species (Ricevuto et al., 2015). Illumatobacter, together with Ruegeria and Nocardioides are denitrifying bacteria (Uchino et al., 1998; Jung et al., 2012), which coupled with sulfide-oxidizing (Arcobacter) (Callbeck et al., 2019), Sammox (Ralstonia) (Li et al., 2020), and sulfate-reducing bacteria (Desulfocarbo indianensis) (Olivera et al., 2022; Table S6) could be cooperating in the removal nitrogen waste products (Deng et al., 2022), accumulating within the borrowed chambers of P. hoplura. These nutrient recycling, waste processing, and detoxifying microbial mechanisms may be pivotal in the adaptation of shell-boring Polydora to their endolithic habitats. Microbial community structures in Polydora hoplura were rather dispersive and heterogeneous across samples, with respect to the more homogeneous microbiomes of corals and sponges, used as comparison. Indeed, corals, sponges, but also other invertebrates are known to possess rich symbiotic microbial compartments, strictly structured by host species (Moitinho-Silva et al., 2017; Dunphy et al., 2019), which play key roles in holobionts’ fitness and physiology (Bourne et al., 2016; Pita et al., 2018; Dittami et al., 2021). Microbial shifts take place under unstable conditions, as means of acclimatization responses (Efremova et al., 2024), where vital functionalities are maintained, thanks to the prevalence of beneficial strains exerting metabolic redundancy (Fan et al., 2013). Variable microbiomes, though, can also indicate incorporation of opportunists, related to stress-induced microbial unbalances –dysbiosis (Corinaldesi et al., 2022). But furthermore, in hosts where symbionts are mostly acquired from the environment (rather than vertically inherited across generations), as is the case of polychaetes, including tubeworms Hydroides elegans (Vijayan et al., 2019) and Diopatra cuprea (Fuirst et al., 2021), or oysters like Magallana gigas, Crassostrea corteziensis and Saccostrea glomerata (Paillard et al., 2022; Unzueta-Martínez et al., 2022), there is a tendency to develop more inconsistent microbiomes. On this line, our polychaete samples, revealing high microbial intraspecific variability of probable horizontal acquisition, offer a great chance of introducing opportunistic and pathogenic strains. At present no published data was available on microbiomes associated with shell-boring polychaetes. However, their flat oyster hots are known to acquire a plethora of microorganisms as a result of their filterfeeding lifestyle (Dittami et al., 2021; Paillard et al., 2022; UnzuetaMartínez et al., 2022). Oysters’ bacterial communities take part of two categories: (i) indigenous taxa, stable over time, and (ii) non-indigenous microbes, comprising potential pathogens (Trabal et al., 2012); with Proteobacteria and Cyanobacteria being the most abundant phyla (Pierce and Ward, 2018; Dittami et al., 2021; Unzueta-Martínez et al., 2022). In correlation with this, the microbial communities in P. hoplura collected from flat oysters, were dominated by Proteobacteria, and included representation of pathogenic strains (Table S6), along with potentially opportunistic and/or pathogenic genera. These encompassed: Vibrio present in variable incidence across samples, Mycobacterium which was the most prevalent genus, and Aliiroseovarius which was unevenly distributed across a few worms, but was the second most represented genus in relative abundance. Vibrio spp. comprise problematic germs for human beings and marine species –including bivalves (Baker-Austin et al., 2018). Such is the case of Vibrio aestuarianus and V. splendidus associated with mortality outbreaks in farmed oysters (Coyle et al., 2023). Polydorid worms here revealed sequences ascribed to V. splendidus together with the also pathogenic V. tapetis (Gatesoupe et al., 1999; Allam et al., 2002; Gómez-León et al., 2005), occurring in various individuals (Table S6). Pathogenic Vibrio, profit from any microbiome destabilization to induce infection, as exemplified during the oyster disease triggered by the Ostreid herpesvirus (OsHV-1 μVar) (Rubio et al., 2019; Clerissi et al., 2020). Similarly, Vibrio spp. tend to proliferate in the bivalves Magallana gigas and Mytilus galloprovincialis after depuration practices, when other symbiotic microbes are removed by the treatment (Vezzulli et al., 2018). In a few cases of mortality events, Vibrio spp. can co-occur with other pathogens. For example, during lethal outbreaks affecting the pen shell Pinna nobilis, Carella et al. (2020) reported the co-occurrence of Mycobacterium, Haplosporidium, Vibrio spp., and other pathogenic taxa in moribund individuals from Italy and Spain. Similarly, Prado et al. (2020) reported three cases of coinfection of Vibrio mediterranei and Mycobacterium sp. in diseased bivalves of the same host species from Spain. Mycobacterium and Haplosporidium pinnae were also associated with inflammatory responses in P. nobilis in the Aegean Sea (Lattos et al., 2021); whereas in the Tyrrhenian Sea (Campania and Sicily) an unidentified Mycobacterium sp. was detected in affected tissues of mortally ill specimens (Carella et al., 2019). Mycobacterium sp. was also the causative agent of orange nodular lesions in the Atlantic sea scallop (Placopecten magellanicus) (Grimm et al., 2016). Actually, Mycobacterium (phylum Actinomycetota) is a quite virulent genus for humans, farmed species, and wildlife from terrestrial and marine environments (Davidovich et al., 2020). Finally, in genus Aliiroseovarius (phylum Pseudomonadota), A. crassostreae was proposed to be the etiologic agent of juvenile oyster disease, which caused deadliness exceeding 90 % among hatchery-produced juvenile Crassostrea virginica in the north-eastern United States (Boettcher et al., 2005; Kessner et al., 2016). The prevalence of these three genera in flat oyster boring P. hoplura, suggests that these worms could act as vectors in the propagation of emerging diseases, carrying health risks for oysters’ production. The physico-chemical changes generated by Polydora on the oyster shell, and consequently in the soft tissues (Haigler, 1969; Blake and Evans, 1973), could be causative for the introduction of opportunistic and pathogenic bacteria. These worms, living within excavated calcareous chambers of the valves, fill their burrows with mud and fecal deposits. Each burrow opens to the outside via an 8-shaped hollow, providing an entrance to microbes that ferment and metabolize these waste materials (Radashevsky and Migotto, 2017). As a result of these microbial anaerobic activities, hydrogen sulfide is accumulated within the chambers, and is drained into the paleal cavity. These acidic fluxes alter the pH, influencing the microbial communities in Polydora worms, but also may destabilize the oyster host microbiome (Handley, 1995; Handley and Bergquist, 1997). Consequently, indigenous bacteria may be replaced by non-indigenous bacteria, including the entrance of transient, innocuous, opportunistic or pathogenic taxa.
5. Conclusions
Polydora hoplura is a worldwide distributed shell-boring pest, with still undetermined geographic origin (Radashevsky and Migotto, 2017; Radashevsky et al., 2023). We provide the first COI barcodes from the type locality, revealing three haplotypes, differing by up to ten nucleotides with each other, indicating introductions from distant populations (Malan et al., 2020). The microbial communities associated with these polychaete worms exhibit notable instability, contrasting the more structured microbiomes of corals and sponges (Moitinho-Silva et al., 2017; Dunphy et al., 2019). Moreover, the presence of opportunistic and potentially pathogenic taxa denotes important environmental inputs (Vijayan et al., 2019; Fuirst et al., 2021). It is plausible that bacterialderived reduced (acidic) sulfur products (sulfide) being poured into the paleal cavity through polydorid chambers may destabilize flat oyster host microbiomes (Handley, 1995; Handley and Bergquist, 1997; Radashevsky and Migotto, 2017). Indeed, the presence of genera like Mycobacterium, Vibrio and Aliiroseovarius entail potential implications for the health of the oyster local populations, and the commercial market (Frias-Lopez et al., 2002; Coenye et al., 2003; Boettcher et al., 2005; Wassenaar and Newell, 2006; Baker-Austin et al., 2018; Davidovich et al., 2020). Further research is needed to evaluate the functional roles of microbial associates in boring Polydora holobionts fitness, and the interactions and consequences of these microorganisms on their oyster host, and eventual human consumers. Funding Funder: Project was partially funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 - Call for tender No. 3138 of 16 December 2021, rectified by Decree n.3175 of 18 December 2021 of Italian Ministry of University and Research funded by the European Union – NextGenerationEU: Award Number: Project code CN_00000033, Concession Decree No. 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, CUP C63C22000520001, Project title “National Biodiversity Future Center – NBFC”. CRediT authorship contribution statement Laura Núñez-Pons: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization. Valerio Mazzella: Writing – review & editing, Writing – original draft, Methodology, Investigation. Lucas Pfingsten: Writing – review & editing, Writing – original draft, Methodology. Mario Santoro: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Declaration of competing interest The authors have no conflicts of interest to declare. Data availability The datasets generated for this study can be found in the NCBI database https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1067543/, and under the accession numbers SAMN39529903–SAMN39529910. Polydora sequences can be found under the accession numbers OQ626355–OQ626367.
Acknowledgements
Thanks are due to M. Mirabella for English proof reading and support in stats tables and L. M. Cusano for image formatting.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi. org/10.1016/j.aquaculture.2024.741522.
Article Images (0)
×![]()
Bioz is the world’s most comprehensive AI search engine for scientific experimentation. The Bioz search engine offers researchers billions of data-driven product, technique, and protocol recommendations. Bioz taps into the latest advances in Artificial Intelligence (AI) – including Natural Language Processing (NLP), Machine Learning (ML) and Generative AI to mine and structure hundreds of millions of pages of complex and unstructured scientific papers. By harnessing the power of AI, Bioz provides researchers with an unprecedented amount of summarized scientific experimentation knowledge right at their fingertips, ultimately helping to speed up drug discovery and the rate of success in finding cures for diseases. Bioz is used by over 15 Million researchers from over 17,000 different universities and companies in 196 countries.
