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Lazarevic V, Whiteson K, Gaïa N, et al. Analysis of the salivary microbiome using culture-independent techniques. J Clin Bioinforma. 2012;2:4doi: 10.1186/2043-9113-2-4.
Lazarevic, V., Whiteson, K., Gaïa, N., Gizard, Y., Hernandez, D., Farinelli, L., Osterås, M., François, P., & Schrenzel, J. (2012). Analysis of the salivary microbiome using culture-independent techniques. Journal of clinical bioinformatics, 24. https://doi.org/10.1186/2043-9113-2-4
Lazarevic, Vladimir, et al. "Analysis of the salivary microbiome using culture-independent techniques." Journal of clinical bioinformatics vol. 2 (2012): 4. doi: https://doi.org/10.1186/2043-9113-2-4
Lazarevic V, Whiteson K, Gaïa N, Gizard Y, Hernandez D, Farinelli L, Osterås M, François P, Schrenzel J. Analysis of the salivary microbiome using culture-independent techniques. J Clin Bioinforma. 2012 Feb 02;2:4. doi: 10.1186/2043-9113-2-4. PMID: 22300522; PMCID: PMC3296672.
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J Clin Bioinforma. 2012 Feb 02;2:4. doi: 10.1186/2043-9113-2-4.

Analysis of the salivary microbiome using culture-independent techniques.

Journal of clinical bioinformatics

Vladimir Lazarevic, Katrine Whiteson, Nadia Gaïa, Yann Gizard, David Hernandez, Laurent Farinelli, Magne Osterås, Patrice François, Jacques Schrenzel

Affiliations

  1. Genomic Research Laboratory, Division of Infectious Diseases, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, CH-1211 Geneva 14, Switzerland. [email protected].

PMID: 22300522 PMCID: PMC3296672 DOI: 10.1186/2043-9113-2-4

Abstract

BACKGROUND: The salivary microbiota is a potential diagnostic indicator of several diseases. Culture-independent techniques are required to study the salivary microbial community since many of its members have not been cultivated.

METHODS: We explored the bacterial community composition in the saliva sample using metagenomic whole genome shotgun (WGS) sequencing, the extraction of 16S rRNA gene fragments from metagenomic sequences (16S-WGS) and high-throughput sequencing of PCR-amplified bacterial 16S rDNA gene (16S-HTS) regions V1 and V3.

RESULTS: The hierarchical clustering of data based on the relative abundance of bacterial genera revealed that distances between 16S-HTS datasets for V1 and V3 regions were greater than those obtained for the same V region with different numbers of PCR cycles. Datasets generated by 16S-HTS and 16S-WGS were even more distant. Finally, comparison of WGS and 16S-based datasets revealed the highest dissimilarity.The analysis of the 16S-HTS, WGS and 16S-WGS datasets revealed 206, 56 and 39 bacterial genera, respectively, 124 of which have not been previously identified in salivary microbiomes. A large fraction of DNA extracted from saliva corresponded to human DNA. Based on sequence similarity search against completely sequenced genomes, bacterial and viral sequences represented 0.73% and 0.0036% of the salivary metagenome, respectively. Several sequence reads were identified as parts of the human herpesvirus 7.

CONCLUSIONS: Analysis of the salivary metagenome may have implications in diagnostics e.g. in detection of microorganisms and viruses without designing specific tests for each pathogen.

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