Sediment Microbiota in Response to Circuitry of Sediment Microbial Fuel Cells, Revealed by 16S rRNA Gene Amplicon Sequencing.
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ABSTRACT:
SUBMITTER: Takemura Y
PROVIDER: S-EPMC8601140 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundRabbit can produce meat, fur and leather, and serves as an important biomedical animal model. Understanding the microbial community of rabbits helps to raise rabbits healthily and better support their application as animal models.ResultsIn this study, we selected 4 healthy Belgium gray rabbits to collect the microbial samples from 12 body sites, including skin, lung, uterus, mouth, stomach, duodenum, ileum, jejunum, colon, cecum, cecal appendix and rectum. The microbiota across rabbit whole body was investigated via 16S rRNA gene amplicon sequencing. After quality control, 46 samples were retained, and 3,148 qualified ASVs were obtained, representing 23 phyla and 264 genera. Based on the weighted UniFrac distances, these samples were divided into the large intestine (Lin), stomach and small intestine (SSin), uterus (Uter), and skin, mouth and lung (SML) groups. The diversity of Lin microbiota was the highest, followed by those of the SSin, Uter and SML groups. In the whole body, Firmicutes (62.37%), Proteobacteria (13.44%) and Bacteroidota (11.84%) were the most predominant phyla. The relative abundance of Firmicutes in the intestinal tract was significantly higher than that in the non-intestinal site, while Proteobacteria was significantly higher in the non-intestinal site. Among the 264 genera, 35 were the core microbiota distributed in all body sites. Sixty-one genera were specific in the SML group, while 13, 8 and 1 were specifically found in the Lin, SSin and Uter groups, respectively. The Lin group had the most difference with other groups, there were average 72 differential genera between the Lin and other groups. The functional prediction analysis showed that microbial function within each group was similar, but there was a big difference between the intestinal tracts and the non-intestinal group. Notably, the function of microorganism in uterus and mouth were the most different from those in the gastrointestinal sites; rabbit's coprophagy of consuming soft feces possibly resulted in little differences of microbial function between stomach and large intestinal sites.ConclusionOur findings improve the knowledge about rabbit microbial communities throughout whole body and give insights into the relationship of microbial communities among different body sites in health rabbits.
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Project description:Microbial amplicon sequencing studies are an important tool in biological and biomedical research. Widespread 16S rRNA gene microbial surveys have shed light on the structure of many ecosystems inhabited by bacteria, including the human body. However, specialized software and algorithms are needed to convert raw sequencing data into biologically meaningful information (i.e. tables of bacterial counts). While different bioinformatic pipelines are available in a rapidly changing and improving field, users are often unaware of limitations and biases associated with individual pipelines and there is a lack of agreement regarding best practices. Here, we compared six bioinformatic pipelines for the analysis of amplicon sequence data: three OTU-level flows (QIIME-uclust, MOTHUR, and USEARCH-UPARSE) and three ASV-level (DADA2, Qiime2-Deblur, and USEARCH-UNOISE3). We tested workflows with different quality control options, clustering algorithms, and cutoff parameters on a mock community as well as on a large (N = 2170) recently published fecal sample dataset from the multi-ethnic HELIUS study. We assessed the sensitivity, specificity, and degree of consensus of the different outputs. DADA2 offered the best sensitivity, at the expense of decreased specificity compared to USEARCH-UNOISE3 and Qiime2-Deblur. USEARCH-UNOISE3 showed the best balance between resolution and specificity. OTU-level USEARCH-UPARSE and MOTHUR performed well, but with lower specificity than ASV-level pipelines. QIIME-uclust produced large number of spurious OTUs as well as inflated alpha-diversity measures and should be avoided in future studies. This study provides guidance for researchers using amplicon sequencing to gain biological insights.
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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.
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Project description:Benthic microbial diversity in Tongyeong, South Korea, was analyzed using next-generation sequencing of the 16S rRNA genes, to reveal the effects of seasonal variations on the microbial community in sediment. Proteobacteria was the dominant phylum, with a relative abundance of 61.5 to 68.1%.
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Project description:Contaminated aquifer (Dusseldorf-Flinger, Germany) templates extracted from 5 sediment depths ranging between 6.4 and 8.4 m below ground and over 3 years of sampling were amplified for amplicon pyrosequencing using the primers Ba27f (5’-aga gtt tga tcm tgg ctc ag-3’) and Ba519r (5’- tat tac cgc ggc kgc tg-3’), extended as amplicon fusion primers with respective primer A or B adapters, key sequence and multiplex identifiers (MID) as recommended by 454/Roche. Amplicons were purified and pooled as specified by the manufacturer. Emulsion PCR (emPCR), purification of DNA-enriched beads and sequencing run were performed following protocols and using a 2nd generation pyrosequencer (454 GS FLX Titanium, Roche) as recommended by the developer. Quality filtering of the pyrosequencing reads was performed using the automatic amplicon pipeline of the GS Run Processor (Roche), with a slight modification concerning the valley filter (vfScanAllFlows false instead of TiOnly) to extract the sequences. Demultiplexed raw reads were furhter trimmed for quality and lenght (>250 bp).
2012-11-11 | GSE25345 | GEO
Project description:Contaminated aquifer (Dusseldorf-Flinger, Germany) templates extracted from 5 sediment depths ranging between 6.4 and 8.4 m below ground and over 3 years of sampling were amplified for amplicon pyrosequencing using the primers Ba27f (5’-aga gtt tga tcm tgg ctc ag-3’) and Ba519r (5’- tat tac cgc ggc kgc tg-3’), extended as amplicon fusion primers with respective primer A or B adapters, key sequence and multiplex identifiers (MID) as recommended by 454/Roche. Amplicons were purified and pooled as specified by the manufacturer. Emulsion PCR (emPCR), purification of DNA-enriched beads and sequencing run were performed following protocols and using a 2nd generation pyrosequencer (454 GS FLX Titanium, Roche) as recommended by the developer. Quality filtering of the pyrosequencing reads was performed using the automatic amplicon pipeline of the GS Run Processor (Roche), with a slight modification concerning the valley filter (vfScanAllFlows false instead of TiOnly) to extract the sequences. Demultiplexed raw reads were furhter trimmed for quality and lenght (>250 bp). 15 samples examined in total from important plume zones of the aquifer sampled in Feb. 2006, Sep. 2008 and Jun. 2009 (5 every year of sampling).
2012-11-11 | E-GEOD-25345 | biostudies-arrayexpress
Project description:Deterioration of sediment quality has been found in the Nakdong River Estuary after large-scale reclamations. Here, I report microbial diversity in sediments of Nakdong River Estuary in the Republic of Korea based on 16S rRNA gene sequencing by next-generation sequencing (NGS) techniques. The dominant bacterial phyla were Proteobacteria, Firmicutes, Bacteroidetes, and Planctomycetes.
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Project description:Antibiotic contamination of the environment negatively affects soil fertility by disrupting natural microbial communities. Currently, the study of the effect of antibacterial drugs on soils typical in Russia, which are of great importance for agriculture, is insufficient. Despite a rapid increase in the number of metagenomic studies, this article is the first publication devoted to the microbial diversity of sod-podzolic soil and its relationship with enzymatic activity. In the present study, we use 16S rRNA metagenomic sequencing to analyze microbiota dynamics and to examine soil enzymatic activities after antibiotic treatment with benzylpenicillin, oxytetracycline, and tylosin. We found that, following treatment, urease activity was reduced regardless of the antibiotic used while nitrification activity showed no statistically significant changes (p > 0.05). Oxytetracycline and tylosin produced no effect on catalase activity but benzylpenicillin caused an increase. Benzylpenicillin and oxytetracycline increased cellulolytic activity whereas tylosin had no significant effect (p > 0.05). Microbiome profiling through 16S rRNA gene sequencing demonstrated antibiotic administration and exhibited no significant impact on bacterial abundance and species diversity (p > 0.05), thus pointing to the resilience of the soil microbial community. Oxytetracycline, benzylpenicillin, and tylosin are likely to negatively affect the enzymatic profiles in sod-podzolic soil but with a negligible influence on the bacterial composition.
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