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Analysis of the Microbial Community Structure in Coastal Sediment of an Ascidian Farm in South Korea through 16S rRNA Gene Amplicon Sequencing.

ABSTRACT: Aquaculture places contamination pressure on the coastal environment. We investigated the microbial community structure changes in sediment in an ascidian Styela clava farm. Data profiling of the 16S rRNA gene amplicon sequence shows that the microbial diversity of sediment in the Styela clava farm is dominated by Proteobacteria (relative abundance, 95.34 to 97.85%).

SUBMITTER: Jeong I

PROVIDER: S-EPMC8320462 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSequential membrane filtration as a pre-processing step for capturing sediment-associated microorganisms could provide good quality and integrity DNA that can be preserved and kept at ambient temperatures before community profiling through culture-independent molecular techniques. However, the effects of sample pre-processing via filtration on DNA-based profiling of sediment-associated microbial community diversity and composition are poorly understood. Specifically, the influences of pre-processing on the quality and quantity of extracted DNA, high-throughput DNA sequencing reads, and detected microbial taxa need further evaluation.ResultsWe assessed the impact of pre-processing freshwater sediment samples by sequential membrane filtration (from 10, 5 to 0.22 μm pore size) for 16S rRNA-based community profiling of sediment-associated microorganisms. Specifically, we examined if there would be method-driven differences between non- and pre-processed sediment samples regarding the quality and quantity of extracted DNA, PCR amplicon, resulting high-throughput sequencing reads, microbial diversity, and community composition. We found no significant difference in the qualities and quantities of extracted DNA and PCR amplicons, and the read abundance after bioinformatics processing (i.e., denoising and chimeric-read filtering steps) between the two methods. Although the non- and pre-processed sediment samples had more unique than shared amplicon sequence variants (ASVs), we report that their shared ASVs accounted for 74% of both methods' absolute read abundance. More so, at the genus level, the final collection filter identified most of the genera (95% of the reads) captured from the non-processed samples, with a total of 51 false-negative (2%) and 59 false-positive genera (3%). We demonstrate that while there were differences in shared and unique taxa, both methods revealed comparable microbial diversity and community composition.ConclusionsOur observations highlight the feasibility of pre-processing sediment samples for community analysis and the need to further assess sampling strategies to help conceptualize appropriate study designs for sediment-associated microbial community profiling.

Dataset Information

Analysis of the Microbial Community Structure in Coastal Sediment of an Ascidian Farm in South Korea through 16S rRNA Gene Amplicon Sequencing.

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