Spread of Antibiotic Resistance Genes (ARGs) in the marine ecosystem: exploring the relationship between environmental factors and the microbiome, resistome, growth and well-being of farmed mussels

This PhD research explored the complex interactions between farmed mussel (Mytilus galloprovincialis), environmental variables and microbial communities through an integrated, multi-scale approach combining environmental monitoring, biological performance assessment, and high-throughput molecular analyses. The study was structured around four main experimental macro-areas, each addressing critical aspects of sustainability and resilience in mussel aquaculture systems. A metagenomic framework was applied to characterize the mussel-associated microbiota and assess its variation across ecotypes, seasons, and environmental gradients. Taxonomic profiling revealed a diverse and heterogeneous microbial community dominated by Proteobacteria, Cyanobacteria, Firmicutes, and Actinobacteriota, with distinct compositional signatures across different tissue pools. Genus-level analysis identified specific microbial taxa enriched in particular environments or host compartments, highlighting potential biomarkers of ecological or physiological significance. Alpha diversity remained relatively uniform across sample groups, whereas beta diversity analyses (PCoA and db-RDA) uncovered significant seasonal variation and indicated that salinity, temperature, and nitrate concentration were key environmental drivers shaping microbial assemblages. Conversely, host-related factors such as ecotype and Condition Index showed no statistically significant association with microbiota structure, possibly due to limited sample representation. Environmental monitoring was conducted using both in situ sensors and satellite remote sensing. Although technical limitations impaired continuous probe-based data collection at the main sampling site, satellite-derived parameters enabled long-term environmental characterization. A parallel deployment at a secondary site (Vasto) demonstrated the strengths and weaknesses of both monitoring approaches. While temperature data showed high concordance between platforms, salinity and chlorophyll-a values were poorly correlated, underscoring the limitations of satellite sensing in dynamic coastal environments. Nonetheless, the satellite-based strategy was deemed appropriate given the temporal scope of the study and the need to capture seasonal and interannual variability. Shotgun metagenomic sequencing was also employed to explore the mussel resistome, although results were hindered by high host DNA contamination, limiting the ability to detect antimicrobial resistance genes (ARGs) in host tissues. This technical barrier underscores the necessity of improved host DNA depletion methods and alternative sampling strategies (e.g., hemolymph) in future work. Despite this, culture-based screening of riverine water samples identified a broad range of Gram-positive and Gram-negative bacteria harboring clinically relevant resistance phenotypes, including ESBL and carbapenem-tolerant strains such as Klebsiella pneumoniae, Escherichia coli, and Pseudomonas aeruginosa. These findings indicate active dissemination of ARGs in estuarine waters adjacent to mussel farms, likely linked to anthropogenic sources. Overall, this study provides novel insights into the microbial ecology of M. galloprovincialis under real-world aquaculture conditions. It emphasizes the influence of environmental factors on microbiota composition, highlights the need for integrative monitoring systems, and sets the groundwork for future resistome profiling in bivalves. By framing mussels as both sentinels and potential vectors within antimicrobial resistance networks, the research underscores the relevance of microbiome-resistome studies for food safety, aquaculture sustainability, and One Health strategies in the face of climate change and rising antibiotic resistance.