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Fast and accurate average genome size and 16S rRNA gene average copy number computation in metagenomic data.

ABSTRACT: BACKGROUND:Metagenomics caused a quantum leap in microbial ecology. However, the inherent size and complexity of metagenomic data limit its interpretation. The quantification of metagenomic traits in metagenomic analysis workflows has the potential to improve the exploitation of metagenomic data. Metagenomic traits are organisms' characteristics linked to their performance. They are measured at the genomic level taking a random sample of individuals in a community. As such, these traits provide valuable information to uncover microorganisms' ecological patterns. The Average Genome Size (AGS) and the 16S rRNA gene Average Copy Number (ACN) are two highly informative metagenomic traits that reflect microorganisms' ecological strategies as well as the environmental conditions they inhabit. RESULTS:Here, we present the ags.sh and acn.sh tools, which analytically derive the AGS and ACN metagenomic traits. These tools represent an advance on previous approaches to compute the AGS and ACN traits. Benchmarking shows that ags.sh is up to 11 times faster than state-of-the-art tools dedicated to the estimation AGS. Both ags.sh and acn.sh show comparable or higher accuracy than existing tools used to estimate these traits. To exemplify the applicability of both tools, we analyzed the 139 prokaryotic metagenomes of TARA Oceans and revealed the ecological strategies associated with different water layers. CONCLUSION:We took advantage of recent advances in gene annotation to develop the ags.sh and acn.sh tools to combine easy tool usage with fast and accurate performance. Our tools compute the AGS and ACN metagenomic traits on unassembled metagenomes and allow researchers to improve their metagenomic data analysis to gain deeper insights into microorganisms' ecology. The ags.sh and acn.sh tools are publicly available using Docker container technology at https://github.com/pereiramemo/AGS-and-ACN-tools .

SUBMITTER: Pereira-Flores E

PROVIDER: S-EPMC6727555 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Fast and accurate average genome size and 16S rRNA gene average copy number computation in metagenomic data.

Pereira-Flores Emiliano E Glöckner Frank Oliver FO Fernandez-Guerra Antonio A

BMC bioinformatics 20190905 1

<h4>Background</h4>Metagenomics caused a quantum leap in microbial ecology. However, the inherent size and complexity of metagenomic data limit its interpretation. The quantification of metagenomic traits in metagenomic analysis workflows has the potential to improve the exploitation of metagenomic data. Metagenomic traits are organisms' characteristics linked to their performance. They are measured at the genomic level taking a random sample of individuals in a community. As such, these traits ...[more]

PMID: 31488068

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Project description:Clostridium difficile is a major spore-forming environmental pathogen that causes serious health problems in patients undergoing antibiotic therapy. Consequently, reliable and sensitive methods for typing individual strains are required for epidemiological and environmental studies. Ribotyping is generally considered the best method, but it fails to account for sequence diversity which might exist in intergenic 16S-23S rRNA spacer regions (ISRs) within and among strains of this organism. Therefore, this study was undertaken to compare the sequence of each individual ISR in five strains of C. difficile to explore the extent of this diversity and see whether such information might provide the basis for more sensitive and discriminatory strain typing methods. After targeted PCR amplification, cloning, and sequencing, the diversity of the ISRs was used as a measure of rRNA operon copy number. In C. difficile strains 630, ATCC 43593, A, and B, 11, 11, 7, and 8 ISR length variants, respectively, were found (containing different combinations of sequence groups [i to xiii]), suggesting 11, 11, 7, and 8 rrn copies in the respective strains. Many ISRs of the same length differed markedly in their sequences, and some of these were restricted in occurrence to a single strain. Most of these ISRs did not contain any tRNA genes, and only single copies of the tRNA(Ala) gene were found in those that did. The presence of ISR sequence groups (i to xiii) varied between strains, with some found in one, two, three, four, or all five strains. We conclude that the intergenic 16S-23S rRNA spacer regions showed a high degree of diversity, not only among the rrn operons in different strains and different rrn copies in a single strain but also among ISRs of the same length. It appears that C. difficile ISRs vary more at the inter- and intragenic levels than those of other species as determined by empirical comparison of sequences. The precise characterization of these sequences has demonstrated a high level of mosaic sequence block rearrangements that are present or absent in multiple strain-variable rrn copies within and between five different strains of C. difficile.

Dataset Information

Fast and accurate average genome size and 16S rRNA gene average copy number computation in metagenomic data.

Publications

Fast and accurate average genome size and 16S rRNA gene average copy number computation in metagenomic data.

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