Summary The health of sharks, like all organisms, is linked to their microbiome. At the skin interface, sharks have dermal denticles that protrude above the mucus, which may affect the types of microbes that occur here. We characterized the microbiome from the skin of the common thresher shark (Alopias vulpinus) to investigate the structure and composition of the skin microbiome. On average 618 812 (80.9% ± S.D. 0.44%) reads per metagenomic library contained open reading frames; of those, between 7.6% and 12.8% matched known protein sequences. Genera distinguishing the A. vulpinus microbiome from the water column included, Pseudoalteromonas (12.8% ± 4.7 of sequences), Erythrobacter (5. 3% ± 0.5) and Idiomarina (4.2% ± 1.2) and distinguishing gene pathways included, cobalt, zinc and cadmium resistance (2.2% ± 0.1); iron acquisition (1.2% ± 0.1) and ton/tol transport (1.3% ± 0.08). Taxonomic community overlap (100 – dissimilarity index) was greater in the skin microbiome (77.6), relative to the water column microbiome (70.6) and a reference host‐associated microbiome (algae: 71.5). We conclude the A. vulpinus skin microbiome is influenced by filtering processes, including biochemical and biophysical components of the shark skin and result in a structured microbiome.
Background: The vertebrate clade diverged into Chondrichthyes (sharks, rays, and chimeras) and Osteichthyes fishes (bony fishes) approximately 420 mya, with each group accumulating vast anatomical and physiological differences, including skin properties. The skin of Chondrichthyes fishes is covered in dermal denticles, whereas Osteichthyes fishes are covered in scales and are mucous rich. The divergence time among these two fish groups is hypothesized to result in predictable variation among symbionts. Here, using shotgun metagenomics, we test if patterns of diversity in the skin surface microbiome across the two fish clades match predictions made by phylosymbiosis theory. We hypothesize (1) the skin microbiome will be host and clade-specific, (2) evolutionary difference in elasmobranch and teleost will correspond with a concomitant increase in host-microbiome dissimilarity, and (3) the skin structure of the two groups will affect the taxonomic and functional composition of the microbiomes. Results: We show that the taxonomic and functional composition of the microbiomes is host-specific. Teleost fish had lower average microbiome within clade similarity compared to among clade comparison, but their composition is not different among clade in a null based model. Elasmobranch's average similarity within clade was not different than across clade and not different in a null based model of comparison. In the comparison of host distance with microbiome distance, we found that the taxonomic composition of the microbiome was related to host distance for the elasmobranchs, but not the teleost fishes. In comparison, the gene function composition was not related to the host-organism distance for elasmobranchs but was negatively correlated with host distance for teleost fishes.
DNA metabarcoding is an important tool for molecular ecology. However, its effectiveness hinges on the quality of reference sequence databases and classification parameters employed. Here we evaluate the performance of MiFish 12S taxonomic assignments using a case study of California Current Large Marine Ecosystem fishes to determine best practices for metabarcoding. Specifically, we use a taxonomy cross‐validation by identity framework to compare classification performance between a global database comprised of all available sequences and a curated database that only includes sequences of fishes from the California Current Large Marine Ecosystem. We demonstrate that the regional database provides higher assignment accuracy than the comprehensive global database. We also document a tradeoff between accuracy and misclassification across a range of taxonomic cutoff scores, highlighting the importance of parameter selection for taxonomic classification. Furthermore, we compared assignment accuracy with and without the inclusion of additionally generated reference sequences. To this end, we sequenced tissue from 597 species using the MiFish 12S primers, adding 252 species to GenBank's existing 550 California Current Large Marine Ecosystem fish sequences. We then compared species and reads identified from seawater environmental DNA samples using global databases with and without our generated references, and the regional database. The addition of new references allowed for the identification of 16 additional native taxa representing 17.0% of total reads from eDNA samples, including species with vast ecological and economic value. Together these results demonstrate the importance of comprehensive and curated reference databases for effective metabarcoding and the need for locus‐specific validation efforts.
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