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Comparison studies of epiphytic microbial communities associated with different growth regions of Sargassum muticum
- GUO Zhansheng, CHANG Lirong, CHEN Wenjing, HOU Xuguang, SHI Kuntao
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JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2024, 59(11):
31-39.
doi:10.6040/j.issn.1671-9352.0.2023.375
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Sargasum muticum is one of the important species for constructing seaweed beds distributed in the intertidal zone of the Yellow Sea and Bohai Sea of China, with high ecological and economic values. While the basic ecological studies of S. muticum are mainly from a macrocosmic viewpoint, our understanding of their impact on microecology remains limited. In this study, the epiphytic microbial communities associated with different growth regions(including vesicles, blades, stalks and holdfast)of S. muticum collected from the intertidal zone of Jingzi Bay were characterized using high throughput sequencing technology, the natural seawater was served as control. The results showed that the holdfast sample of S. muticum displayed the highest level of microbial richness and diversity, while the lowest microbial richness was in the blade sample, and the microbial diversity and evenness were lower in the vesicle sample than in other growth regions. PCoA and Anosim analyses showed that the structure of the microbial communities on S. muticum is distinct from those of planktonic communities(p<0.05), while no significant differences were observed between different growth regions of S. muticum(p≥0.05). The community structure analysis results showed that Proteobacteria, Firmicute and Bacteroidota were the common predominant phyla, with the relative abundance of 80.51%-87.64%; Yoonia- Loktanella was most dominant genus in the samples from the vesicle, blade and stalk(11.90%-18.02%), the dominant genus of the holdfast samples is Pleurocapsa_ PCC-7319(7.48%). A total of 15 biomarkers were identified using LEfse analysis, of which 5, 1, and 9 biomarkers in the sample groups from vesicle, holdfast and water, respectively. The metagenome function prediction of S. muticum was carried out using Tax4Fun software, metabolism was prominent common function(46.16%-48.35%), followed by genetic information processing(21.18%-22.88%)and environmental information processing(12.03%-13.96%). This study would provide a theoretical basis for in-depth understanding of the ecological characteristics of S. muticum by comparing the epiphytic microbial communities associated with different growth regions of the seaweed.
