The epidermal microbiome is a critical element of marine organismal immunity, but the epidermal virome of marine organisms remains largely unexplored. The epidermis of sharks represents a unique viromic ecosystem. Sharks secrete a thin layer of mucus which harbors a diverse microbiome, while their hydrodynamic dermal denticles simultaneously repel environmental microbes. Here, we sampled the virome from the epidermis of three shark species in the family Carcharhinidae: the genetically and morphologically similar Carcharhinus obscurus (n = 6) and Carcharhinus galapagensis (n = 10) and the outgroup Galeocerdo cuvier (n = 15). Virome taxonomy was characterized using shotgun metagenomics and compared with a suite of multivariate analyses. All three sharks retain species-specific but highly similar epidermal viromes dominated by uncharacterized bacteriophages which vary slightly in proportional abundance within and among shark species. Intraspecific variation was lower among C. galapagensis than among C. obscurus and G. cuvier. Using both the annotated and unannotated reads, we were able to determine that the Carcharhinus galapagensis viromes were more similar to that of G. cuvier than they were to that of C. obscurus, suggesting that behavioral niche may be a more prominent driver of virome than host phylogeny.

Characterizations of shark-microbe systems in wild environments have outlined patterns of species-specific microbiomes; however, whether captivity affects these trends has yet to be determined. We used high-throughput shotgun sequencing to assess the epidermal microbiome belonging to leopard sharks (Triakis semifasciata) in captive (Birch Aquarium, La Jolla California born and held permanently in captivity), semi-captive (held in captivity for <1 year in duration and scheduled for release; Scripps Institute of Oceanography, San Diego, CA, USA) and wild environments (Moss Landing and La Jolla, CA, USA). Here, we report captive environments do not drive epidermal microbiome compositions of T. semifasciata to significantly diverge from wild counterparts as life-long captive sharks maintain a species-specific epidermal microbiome resembling those associated with semi-captive and wild populations. Major taxonomic composition shifts observed were inverse changes of top taxonomic contributors across captive duration, specifically an increase of Pseudoalteromonadaceae and consequent decrease of Pseudomonadaceae relative abundance as T. semifasciata increased duration in captive conditions. Moreover, we show captivity did not lead to significant losses in microbial α-diversity of shark epidermal communities. Finally, we present a novel association between T. semifasciata and the Muricauda genus as Metagenomes associated genomes revealed a consistent relationship across captive, semi-captive, and wild populations. Since changes in microbial communities is often associated with poor health outcomes, our report illustrates that epidermally associated microbes belonging to T. semifasciata are not suffering detrimental impacts from long or short-term captivity. Therefore, conservation programs which house sharks in aquariums are providing a healthy environment for the organisms on display. Our findings also expand on current understanding of shark epidermal microbiomes, explore the effects of ecologically different scenarios on benthic shark microbe associations, and highlight novel associations that are consistent across captive gradients.

Epidermal mucus is a complicated mixture of macromolecules which acts as the first line of defence for organisms against abrasions and infections. We quantified the carbohydrate (monosaccharide) composition of the mucus from four Elasmobranchii hosts, including eagle rays ( Myliobatis tenuicaudatus ), Port Jackson sharks ( Heterodontus portusjacksoni ), Australian angelsharks ( Squatina australis ) and whitespotted skates ( Dentiraja cerva ). Elasmobranchii had low amounts of mucus and a low proportion of carbohydrates (< 10%) compared with other marine organisms. Four key monosaccharides: glucose, glucosamine, galactose and fucose, were identified in mucus samples. Hosts exhibited distinct, species‐specific monosaccharide signatures. We identified key carbohydrate microbial genes from host and water microbiomes. Elasmobranch microbiomes had a higher relative abundance of carbon utilisation genes compared to the water column and contained gene pathways for the utilisation of specific monosaccharides found in host mucus, suggesting that the host mucus was a regulator of the microbiome. Elasmobranch epidermal microbiomes have the genetic machinery required for detecting, transporting and metabolising monosaccharides and other carbohydrates present in the host mucus, demonstrating the selective nature of Elasmobranch epidermal mucus.

Chronic infections in cystic fibrosis (CF) emerge from gradual ecological transitions in the airway microbiome, yet early predictive markers remain poorly defined. We developed a new autoencoder-based framework that outperforms read-based or metagenome-assembled genome-based analyses at capturing the continuum from health-associated commensals to pathogen-dominated, antibiotic-tolerant communities. This improvement is achieved by integrating taxonomic and functional data from 127 sputum and bronchoalveolar lavage metagenomes from 64 people with CF into latent “Clusters of Phylogeny and Functions” (COPFs). Coupled with gradient-boosted random forests, COPFs predicted Pseudomonas aeruginosa colonisation, multidrug resistance, and impending infection up to a year before clinical detection. The multidrug-resistant P. aeruginosa signature showed the same resistance-mechanism evolution as found in laboratory experiments. The inclusion of eukaryotic markers revealed persistent Aspergillus fumigatus signatures even during culture-negative intervals. Applying our South Australian-trained model to over 1,000 global metagenomes from 22 independent CF datasets, we achieved 94% accuracy in predicting P. aeruginosa status across platforms and geographies, validating the model’s universal utility. Our results demonstrate that combining datasets with deep learning reveals conserved ecological and metabolic mechanisms in disease progression, transforming metagenomics into a predictive framework for managing chronic infections.

Here, we isolated five bacterial species from the skin and cloaca of Carcharodon carcharias (white shark) and Carcharhinus brachyurus (bronze whaler or copper shark).