Characterization of spatial distribution of the bacterial community in the South Sea of Korea

Abstract

In order to investigate the importance of spatial and environmental factors on the structure and diversity of bacterial communities, high-resolution 16S rRNA gene tag pyrosequencing was applied to bacterial communities in the littoral sea. Seawater samples were prepared from seven different stations in the South Sea of Korea, the marginal sea in the western Pacific Ocean, and were divided into three groups according to distances from the coastline. The majority of 19,860 sequences were affiliated with Alphaproteobacteria (58.2%), Gammaproteobacteria (7.9%), and Bacteroidetes (13.9%). The bacterioplankton community at each station was highly diverse and varied among the samples. Major bacterial lineages showed different niche preferences among three locational groups. Alphaproteobacteria was the most abundant bacterial class, and it harbored the most frequently recorded operational taxonomic units (OTUs) in all sampling stations. However, dominant groups at the order levels showed a clear difference among the samples. The SAR11 clade was more abundant in coastal waters while the Roseobacter clade prevailed at stations far away from the coastline. Furthermore, members of Actinobacteria and Cyanobacteria also exhibited spatial variability. The OM1 clade in Actinobacteria constituted a predominant fraction in coastal samples, but it was essentially absent at the distal stations closer to open ocean. In contrast, Synechococcus was the predominant taxon in the distal samples, accounting for 7.1–19.5%, but was hardly detected in coastal waters, representing less than 0.7%. In Bacteroidetes, NS5 and NS9 groups tended to inhabit coastal waters while the genera Polaribacter and Ulvibacter were more abundant in distal stations. Clustering analysis and principle coordinates analysis based on OTU data indicated that bacterial communities in the studied area were separated into three groups that coincided with locational grouping. Statistical analysis showed that phosphate and dissolved oxygen concentration had a significant influence on the bacterial community composition.

Insights on aquatic microbiome of the Indian Sundarbans mangrove areas

“…However, this is the first report of their abundance in marine water of Sundarbans. The NS5 marine group which are equally dominated in both the studied sites are reported to be ubiquitous in the seawater-related samples and known for phytoplankton-derived macromolecules [47][48][49].…”

High-Quality Draft Single-Cell Genome Sequence of the NS5 Marine Group from the Coastal Red Sea

“…The uncultured N5 marine group (also known as ARC11) represents one of the most ubiquitous flavobacterial bacterioplankton in the pelagic ocean ( 1 – 3 ). Their biomass can reach 6 × 10 3 cells per ml ( 4 ), and their abundance is strongly correlated with marine phytoplankton blooms ( 4 – 6 ).…”

“…Their biomass can reach 6 × 10 3 cells per ml ( 4 ), and their abundance is strongly correlated with marine phytoplankton blooms ( 4 – 6 ). Therefore, members of this group are currently considered indicator species for coastal bacterioplankton communities ( 3 ). However, to date no member of NS5 has been cultivated or sequenced.…”

Temporal and Vertical Variation in Microbial Community Composition in Response to Physicochemical Characteristics in a Water Column of Highly Eutrophied Jinhae Bay, South Korea

“…After processing, the clean reads were analyzed using the open-source QIIME software package (v.1) [Caporaso et al, 2010] according to the default parameters for the samples by grouping them into surface, middle, and bottom layers according to the specific objectives of the analyses. Based on previous metagenome analysis [Liu et al, 2015;Laas et al, 2016;Seo et al, 2017], OTUs corresponding to each read were chosen at 97% similarity against the Greengenes 16S rRNA database and matched with known microbial genomes to identify members of the microbial community. Cluster analysis and PCoA graphs were constructed in the Calypso online software (v.8.44) (http://cgenome.net/wiki/index.php/Calypso) [Zakrzewski et al, 2017].…”