Dataset Information

VITCOMIC: visualization tool for taxonomic compositions of microbial communities based on 16S rRNA gene sequences.

ABSTRACT: BACKGROUND: Understanding the community structure of microbes is typically accomplished by sequencing 16S ribosomal RNA (16S rRNA) genes. These community data can be represented by constructing a phylogenetic tree and comparing it with other samples using statistical methods. However, owing to high computational complexity, these methods are insufficient to effectively analyze the millions of sequences produced by new sequencing technologies such as pyrosequencing. RESULTS: We introduce a web tool named VITCOMIC (VIsualization tool for Taxonomic COmpositions of MIcrobial Community) that can analyze millions of bacterial 16S rRNA gene sequences and calculate the overall taxonomic composition for a microbial community. The 16S rRNA gene sequences of genome-sequenced strains are used as references to identify the nearest relative of each sample sequence. With this information, VITCOMIC plots all sequences in a single figure and indicates relative evolutionary distances. CONCLUSIONS: VITCOMIC yields a clear representation of the overall taxonomic composition of each sample and facilitates an intuitive understanding of differences in community structure between samples. VITCOMIC is freely available at http://mg.bio.titech.ac.jp/vitcomic/.

SUBMITTER: Mori H

PROVIDER: S-EPMC2894824 | biostudies-other | 2010

REPOSITORIES: biostudies-other

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VITCOMIC: visualization tool for taxonomic compositions of microbial communities based on 16S rRNA gene sequences.

Mori Hiroshi H Maruyama Fumito F Kurokawa Ken K

BMC bioinformatics 20100618

<h4>Background</h4>Understanding the community structure of microbes is typically accomplished by sequencing 16S ribosomal RNA (16S rRNA) genes. These community data can be represented by constructing a phylogenetic tree and comparing it with other samples using statistical methods. However, owing to high computational complexity, these methods are insufficient to effectively analyze the millions of sequences produced by new sequencing technologies such as pyrosequencing.<h4>Results</h4>We intro ...[more]

PMID: 20565810

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Project description:BACKGROUND:The 16S rRNA gene-based amplicon sequencing analysis is widely used to determine the taxonomic composition of microbial communities. Once the taxonomic composition of each community is obtained, evolutionary relationships among taxa are inferred by a phylogenetic tree. Thus, the combined representation of taxonomic composition and phylogenetic relationships among taxa is a powerful method for understanding microbial community structure; however, applying phylogenetic tree-based representation with information on the abundance of thousands or more taxa in each community is a difficult task. For this purpose, we previously developed the tool VITCOMIC (VIsualization tool for Taxonomic COmpositions of MIcrobial Community), which is based on the genome-sequenced microbes' phylogenetic information. Here, we introduce VITCOMIC2, which incorporates substantive improvements over VITCOMIC that were necessary to address several issues associated with 16S rRNA gene-based analysis of microbial communities. RESULTS:We developed VITCOMIC2 to provide (i) sequence identity searches against broad reference taxa including uncultured taxa; (ii) normalization of 16S rRNA gene copy number differences among taxa; (iii) rapid sequence identity searches by applying the graphics processing unit-based sequence identity search tool CLAST; (iv) accurate taxonomic composition inference and nearly full-length 16S rRNA gene sequence reconstructions for metagenomic shotgun sequencing; and (v) an interactive user interface for simultaneous representation of the taxonomic composition of microbial communities and phylogenetic relationships among taxa. We validated the accuracy of processes (ii) and (iv) by using metagenomic shotgun sequencing data from a mock microbial community. CONCLUSIONS:The improvements incorporated into VITCOMIC2 enable users to acquire an intuitive understanding of microbial community composition based on the 16S rRNA gene sequence data obtained from both metagenomic shotgun and amplicon sequencing.

Project description:Hyalomma dromedarii is an important blood-feeding ectoparasite that affects the health of camels. We assessed the profile of bacterial communities associated with H. dromedarii collected from camels in the eastern part of the UAE in 2010 and 2019. A total of 100 partially engorged female ticks were taken from tick samples collected from camels (n = 100; 50/year) and subjected to DNA extraction and sequencing. The 16S rRNA gene was amplified from genomic DNA and sequenced using Illumina MiSeq platform to elucidate the bacterial communities. Principle Coordinates Analysis (PCoA) was conducted to determine patterns of diversity in bacterial communities. In 2010 and 2019, we obtained 899,574 and 781,452 read counts and these formed 371 and 191 operational taxonomic units (OTUs, clustered at 97% similarity), respectively. In both years, twenty-five bacterial families with high relative abundance were detected and the following were the most common: Moraxellaceae, Enterobacteriaceae, Staphylococcaceae, Bacillaceae, Corynebacteriaceae, Flavobacteriaceae, Francisellaceae, Muribaculaceae, Neisseriaceae, and Pseudomonadaceae. Francisellaceae and Enterobacteriaceae coexist in H. dromedarii and we suggest that they thrive under similar conditions and microbial interactions inside the host. Comparisons of diversity indicated that microbial communities differed in terms of richness and evenness between 2010 and 2019, with higher richness but lower evenness in communities in 2010. Principle coordinates analyses showed clear clusters separating microbial communities in 2010 and 2019. The differences in communities suggested that the repertoire of microbial communities have shifted. In particular, the significant increase in dominance of Francisella and the presence of bacterial families containing pathogenic genera shows that H. dromedarii poses a serious health risk to camels and people who interact with them. Thus, it may be wise to introduce active surveillance of key genera that constitute a health hazard in the livestock industry to protect livestock and people.

Project description:ObjectiveThe study of Hanwoo (Korean native cattle) has mainly been focused on meat quality and productivity. Recently the field of microbiome research has increased dramatically. However, the information on the microbiome in Hanwoo is still insufficient, especially relationship between vagina and feces. Therefore, the purpose of this study is to examine the microbial community characteristics by analyzing the 16S rRNA sequencing data of Hanwoo vagina and feces, as well as to confirm the difference and correlation between vaginal and fecal microorganisms. As a result, the goal is to investigate if fecal microbiome can be used to predict vaginal microbiome.MethodsA total of 31 clinically healthy Hanwoo that delivered healthy calves more than once in Cheongju, South Korea were enrolled in this study. During the breeding season, we collected vaginal and fecal samples and sequenced the microbial 16S rRNA genes V3-V4 hypervariable regions from microbial DNA of samples.ResultsThe results revealed that the phylum-level microorganisms with the largest relative distribution were Firmicutes, Actinobacteria, Bacteroidetes, and Proteobacteria in the vagina, and Firmicutes, Bacteroidetes, and Spirochaetes in the feces, respectively. In the analysis of alpha, beta diversity, and effect size measurements (LefSe), the results showed significant differences between the vaginal and fecal samples. We also identified the function of these differentially abundant microorganisms by functional annotation analyses. But there is no significant correlation between vaginal and fecal microbiome.ConclusionThere is a significant difference between vaginal and fecal microbiome, but no significant correlation. Therefore, it is difficult to interrelate vaginal microbiome as fecal microbiome in Hanwoo. In a further study, it will be necessary to identify the genetic relationship of the entire microorganism between vagina and feces through the whole metagenome sequencing analysis and meta-transcriptome analysis to figure out their relationship.

Dataset Information

VITCOMIC: visualization tool for taxonomic compositions of microbial communities based on 16S rRNA gene sequences.

Publications

VITCOMIC: visualization tool for taxonomic compositions of microbial communities based on 16S rRNA gene sequences.

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