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:Background. 16S rRNA gene sequences are routinely assigned to operational taxonomic units (OTUs) that are then used to analyze complex microbial communities. A number of methods have been employed to carry out the assignment of 16S rRNA gene sequences to OTUs leading to confusion over which method is optimal. A recent study suggested that a clustering method should be selected based on its ability to generate stable OTU assignments that do not change as additional sequences are added to the dataset. In contrast, we contend that the quality of the OTU assignments, the ability of the method to properly represent the distances between the sequences, is more important. Methods. Our analysis implemented six de novo clustering algorithms including the single linkage, complete linkage, average linkage, abundance-based greedy clustering, distance-based greedy clustering, and Swarm and the open and closed-reference methods. Using two previously published datasets we used the Matthew's Correlation Coefficient (MCC) to assess the stability and quality of OTU assignments. Results. The stability of OTU assignments did not reflect the quality of the assignments. Depending on the dataset being analyzed, the average linkage and the distance and abundance-based greedy clustering methods generated OTUs that were more likely to represent the actual distances between sequences than the open and closed-reference methods. We also demonstrated that for the greedy algorithms VSEARCH produced assignments that were comparable to those produced by USEARCH making VSEARCH a viable free and open source alternative to USEARCH. Further interrogation of the reference-based methods indicated that when USEARCH or VSEARCH were used to identify the closest reference, the OTU assignments were sensitive to the order of the reference sequences because the reference sequences can be identical over the region being considered. More troubling was the observation that while both USEARCH and VSEARCH have a high level of sensitivity to detect reference sequences, the specificity of those matches was poor relative to the true best match. Discussion. Our analysis calls into question the quality and stability of OTU assignments generated by the open and closed-reference methods as implemented in current version of QIIME. This study demonstrates that de novo methods are the optimal method of assigning sequences into OTUs and that the quality of these assignments needs to be assessed for multiple methods to identify the optimal clustering method for a particular dataset.

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.

Similar Datasets

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