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Int J Syst Evol Microbiol. 2017 Jun;67(6):2053-2057. doi: 10.1099/ijsem.0.001872. Epub 2017 Jun 22.

ContEst16S: an algorithm that identifies contaminated prokaryotic genomes using 16S RNA gene sequences.

Author information

1
1​School of Biological Sciences & Institute of Molecular Biology & Genetics, Seoul National University, Seoul 151-742, Republic of Korea.
2
2​Inter-disciplinary Program in Bioinformatics, Seoul National University, Seoul 151-742, Republic of Korea.
3
3​ChunLab, Inc., Seoul National University, Seoul 151-742, Republic of Korea 1​School of Biological Sciences & Institute of Molecular Biology & Genetics, Seoul National University, Seoul 151-742, Republic of Korea.
4
3​ChunLab, Inc., Seoul National University, Seoul 151-742, Republic of Korea 2​Inter-disciplinary Program in Bioinformatics, Seoul National University, Seoul 151-742, Republic of Korea 1​School of Biological Sciences & Institute of Molecular Biology & Genetics, Seoul National University, Seoul 151-742, Republic of Korea.

Abstract

Thanks to the recent advancement of DNA sequencing technology, the cost and time of prokaryotic genome sequencing have been dramatically decreased. It has repeatedly been reported that genome sequencing using high-throughput next-generation sequencing is prone to contaminations due to its high depth of sequencing coverage. Although a few bioinformatics tools are available to detect potential contaminations, these have inherited limitations as they only use protein-coding genes. Here we introduce a new algorithm, called ContEst16S, to detect potential contaminations using 16S rRNA genes from genome assemblies. We screened 69 745 prokaryotic genomes from the NCBI Assembly Database using ContEst16S and found that 594 were contaminated by bacteria, human and plants. Of the predicted contaminated genomes, 8 % were not predicted by the existing protein-coding gene-based tool, implying that both methods can be complementary in the detection of contaminations. A web-based service of the algorithm is available at www.ezbiocloud.net/tools/contest16s.

PMID:
28639931
DOI:
10.1099/ijsem.0.001872
[Indexed for MEDLINE]

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