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. 2023 Apr 11;5(1):23.
doi: 10.1186/s42523-023-00245-9.

The mycobiome of a successful crayfish invader and its changes along the environmental gradient

Affiliations

The mycobiome of a successful crayfish invader and its changes along the environmental gradient

Paula Dragičević et al. Anim Microbiome. .

Abstract

Background: The microbiome plays an important role in biological invasions, since it affects various interactions between host and environment. However, most studies focus on the bacteriome, insufficiently addressing other components of the microbiome such as the mycobiome. Microbial fungi are among the most damaging pathogens in freshwater crayfish populations, colonizing and infecting both native and invasive crayfish species. Invading crayfish may transmit novel fungal species to native populations, but also, dispersal process and characteristics of the novel environment may affect the invaders' mycobiome composition, directly and indirectly affecting their fitness and invasion success. This study analyzes the mycobiome of a successful invader in Europe, the signal crayfish, using the ITS rRNA amplicon sequencing approach. We explored the mycobiomes of crayfish samples (exoskeletal biofilm, hemolymph, hepatopancreas, intestine), compared them to environmental samples (water, sediment), and examined the differences in fungal diversity and abundance between upstream and downstream segments of the signal crayfish invasion range in the Korana River, Croatia.

Results: A low number of ASVs (indicating low abundance and/or diversity of fungal taxa) was obtained in hemolymph and hepatopancreas samples. Thus, only exoskeleton, intestine, sediment and water samples were analyzed further. Significant differences were recorded between their mycobiomes, confirming their uniqueness. Generally, environmental mycobiomes showed higher diversity than crayfish-associated mycobiomes. The intestinal mycobiome showed significantly lower richness compared to other mycobiomes. Significant differences in the diversity of sediment and exoskeletal mycobiomes were recorded between different river segments (but not for water and intestinal mycobiomes). Together with the high observed portion of shared ASVs between sediment and exoskeleton, this indicates that the environment (i.e. sediment mycobiome) at least partly shapes the exoskeletal mycobiome of crayfish.

Conclusion: This study presents the first data on crayfish-associated fungal communities across different tissues, which is valuable given the lack of studies on the crayfish mycobiome. We demonstrate significant differences in the crayfish exoskeletal mycobiome along the invasion range, suggesting that different local environmental conditions may shape the exoskeletal mycobiome during range expansion, while the mycobiome of the internal organ (intestine) remained more stable. Our results provide a basis for assessing how the mycobiome contributes to the overall health of the signal crayfish and its further invasion success.

Keywords: Fungi; ITS rRNA gene; Invasive species; Microbiome; Pacifastacus leniusculus.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Alpha diversity analyses showing (A) the number of observed features and (B) the Pielou’s evenness index for mycobiomes from different sample groups. Significant differences are marked with different letters
Fig. 2
Fig. 2
Beta diversity analyses of mycobiomes between different sample groups. The PcoAs are based on (A) Jaccard and (B) Bray-Curtis distance matrices
Fig. 3
Fig. 3
Relative abundance (%) of the overall most prevalent genera of all four sample groups. ASVs that could not be identified to genus (g) level are marked with the letter corresponding to the last known taxonomic level (p = phylum, o = order, f = family). Fungal taxa with a total abundance of > 3% are shown, while the remaining taxa were pooled and marked as “other.” ASVs to which taxonomy could not be assigned were pooled and marked as „unassigned“
Fig. 4
Fig. 4
Venn diagrams showing the numbers of shared and unique ASVs between four sample groups. The total number of ASVs in each sample group is marked with n
Fig. 5
Fig. 5
Beta diversity analyses of (A,C) sediment and (B,D) exoskeletal mycobiomes between upstream and downstream river segments. The PcoAs are based on (A,B) Jaccard and (C,D) Bray-Curtis distance matrices

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