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Comparative analysis of microbial communities, assembly processes, and life-history strategies in a mariculture-impacted eutrophic bay and adjacent coastal sediments.

Sep 2026 · Ecotoxicology and Environmental Safety · Vol 323, pp. 120750 · 0 citations · 120 references
Medicine

Abstract

Coastal embayments are increasingly subjected to intensive mariculture, which delivers sustained nutrient, organic matter, and antibiotics to sediments, yet microbiome responses remain poorly understood. Here we compared sediment microbiomes of the eutrophic Xiangshan Bay (XSB) and oligotrophic East China Sea (ECS), integrating cell counts, 16S rRNA amplicon, metagenomics, and cultivation-based resistance assays. Cell counts and amplicon data showed that XSB harbored higher microbial abundance (1.28 ×108-1.34 ×109 vs. 2.07 ×107-4.43 ×108 cells g⁻¹), Chao1 richness (10,374-16,674 vs. 8311-12,281), and Shannon diversity (6.31-7.43 vs. 5.95-6.68). Amplicon-based null and neutral models indicated that community assembly in XSB was less stochastic and more deterministically selected than in the ECS. Life-history traits inferred directly from metagenomic data were consistently elevated in XSB relative to ECS, including 16S rRNA gene copy number (3.35 vs. 2.37), codon usage bias (0.0219 vs. 0.0188), maximum growth potential (0.1208 vs. 0.0844 h-1), genome size (5.63 vs. 5.38 Mb), GC content (56.26% vs. 54.48%), and transposase abundance (3.91% vs. 2.55%), collectively indicating a transition from K- to r-selected life-history strategies. Moreover, metagenomic annotation revealed a similarly expanded resistome in XSB, with 4.5-fold higher antibiotic resistance gene abundance (17.40-45.37 vs. 7.96-25.96 RPM) dominated by efflux-pump mechanisms, while plate assays showed roughly two-fold higher phenotypic resistance to macrolides, tetracyclines, and sulfonamides. These findings demonstrate that microbial community, life-history strategies, and antibiotic resistance respond as a coupled system to mariculture-driven eutrophication, providing a trait-based framework for predicting microbiome trajectories under anthropogenic nutrient enrichment.

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