Fungal communities are diverse and abundant in coastal waters, yet, their ecological roles and adaptations remain largely unknown. To address these gaps, ITS2 metabarcoding and metatranscriptomic analyses were used to capture the whole suite of fungal diversity and their metabolic potential in water column and sediments in the Yellow Sea during August and October 2019. ITS2 metabarcoding described successfully the abundance of Dikarya during August and October at the different examined habitats, but strongly underrepresented or failed to identify other fungal taxa, including zoosporic and early-diverging lineages, that were abundant in the mycobiome as uncovered by metatranscriptomes. Metatranscriptomics also revealed enriched expression of genes annotated to zoosporic fungi (e.g., chytrids) mainly in the surface water column in October. This enriched expression was correlated with the two-fold increase in chlorophyll-a intensity attributed to phytoplanktonic species which are known to be parasitized by chytrids. The concurrent high expression of genes related to calcium signalling and GTPase activity suggested that these metabolic traits facilitate the parasitic lifestyle of chytrids. Similarly, elevated expression of phagosome genes annotated to Rozellomycota, an early-diverging fungal phylum not fully detected with ITS2 metabarcoding, suggested that this taxon utilizes a suite of feeding modes, including phagotrophy in this coastal setting. Our data highlight the necessity of using combined approaches to accurately describe the community structure of coastal mycobiome. We also provide in-depth insights into the fungal ecological roles in coastal waters, and report potential metabolic mechanisms utilized by fungi to cope with environmental stresses that occur during distinct seasonal months in coastal ecosystems.
Keyphrases
- human health
- climate change
- heavy metals
- poor prognosis
- risk assessment
- genome wide
- binding protein
- cell wall
- type diabetes
- metabolic syndrome
- gene expression
- physical activity
- single cell
- radiation therapy
- high intensity
- water quality
- dna methylation
- liquid chromatography
- deep learning
- artificial intelligence
- energy transfer
- bioinformatics analysis
- antibiotic resistance genes
- solid phase extraction
- wastewater treatment
- genome wide analysis