doi: 10.15389/agrobiology.2013.4.76eng

UDC 579.6/.8:631.46:575.852'1

THE CONCEPT OF TAXONOMIC SPACE AND INTEGRAL ESTIMATES OF SHIFT IN THE STRUCTURE OF MICROBIAL COMMUNITY BASED ON ANALYSIS OF 16S rRNA GENE LIBRARIES

E.V. Pershina1, A.S. Dol'nik2, A.G. Pinaev1, K.A. Loshakova1, E.E. Andronov1

1All-Russian Research Institute of Agricultural Microbiology, Russian Academy of Agricultural Sciences,
3, sh. Podbel'skogo, Pushkin-8, St. Petersburg, 196608 Russia,
e-mail: eeandr@gmail.com;
2Saint Petersburg State University,
28, Universitetskii prosp., Staryi Petergof, St. Petersburg, 199034 Russia,
e-mail: alexander.dolnik@gmail.com

Received September 25, 2012

The problem of taxonomic structure and dynamics of soil, plant animal and human microbiomes is one of the most intriguing in modern microbiology. High Performance Technologies sequencing of the 16S rRNA gene allows to get much more metagenomic data, but their correct analysis and biological interpretation are still complicated, in particular with regard to the effect of selective amplification with universal primers and proper attribution of the samples. To resolve the problems, we created a special operating environment, the taxonomic space (TS), in which the sequences of 16S rRNA gene are represented by dots, geometric distance between which corresponds to the genetic distance between the sequences. Mapping the 16S-rRNA gene biodiversity data in this TS and evaluation of the microbial community as overorganism, with its integral parameters, have a number of advantages if compared to the traditional approaches. Thus, in the TS where each sequence of the 16S rRNA gene gets its own identifier of the 42 coordinates, the unattributed amplicons in any PCR-library can be analyzed. Although the described TS is not strictly a multi-dimensional mathematical space, in particular, its axes are interdependent, an extremely high correlation coefficients, obtained for genetic distances between sequences and their geometric counterparts, unconditionally, testify in favor of the validity of the use of TS in practice. The development of TS concept is of great importance not only in the analysis of the structure of microbial communities, but also in imvestigation of 16S rRNA genes evolution. Since the model allows to give a description for any variant, both realized and not yet realized in evolution, the issues related to the origin and divergent evolution of prokaryotes may be investigated, for example, the hypothetical center of origin can be determine, and then the TS will become an evolutionary space. As a model, we used different soil microbiomes in which the changes were induced by environmental conditions (salinity), both natural and simulated. However, the application of this approach can be extended to other complex microbiomes, particularly the microbiota in animals. Moreover, the proposed mathematical method is universal and can be used to study not only biodiversity in prokaryotes, but also the communities of eukaryotic organisms, including animals and plants, with the 18S rRNA gene as a taxonomic marker.

Keywords: microbiom, soil, salinization, 16S rRNA, taxonomic space.

 

Full article (Rus)

Full text (Eng)

 

REFERENCES

1. Tringe S.G., Hugenholtz P. A renaissance for the pioneering 16S rRNA gene. Curr. Opin. Microbiol., 2008, 5(11): 442-446. CrossRef
2. Lauber C.L., Hamady M., Knight R., Fierer N. Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale. Appl. Environ. Microbiol., 2009, 15(75): 5111-5120. CrossRef
3. Lombard N., Prestat E., Elsas J.D.V., Simonet P. Soil-specific limitations for access and analysis of soil microbial communities by metagenomics. FEMS Microbiol. Ecol., 2011, 78: 31-49. CrossRef
4. Hunter C.I., Mitchell A., Jones P. McAnulla C., Pesseat S., Scheremetjew M., Hunter S. Metagenomic analysis: the challenge of the data bonanza. Briefings in Bioinformatics, 2012, 6(13): 743-746. CrossRef
5. Acinas S.G., Sarma-Rupavtarm R., Klepac-Ceraj V., Polz M. PCR-induced sequence artifacts and bias: insights from comparison of two 16S rRNA clone libraries constructed from the same sample. Appl. Environ. Microbiol., 2005, 71 (12): 8966-8969.
6. Sipos R., Székely A.J., Palatinszky M., Révész S., Márialigeti K., Nikolausz M. et al. Effect of primer mismatch, annealing temperature and PCR cycle number on 16S rRNA gene-targeting bacterial community analysis. FEMS Microbiol.
Ecol
., 2007, 2(60): 341-350. CrossRef
7. Bergmann G.T., Bates S.T., Eilers K.G., Lauber C.L., Caporaso J.G., Walters W.A., Knight R., Fierer N. The under-recognized dominance of Verrucomicrobia in soil bacterial communities. Soil Biol. Biochem., 2011, 43: 1450-1455.CrossRef
8. Sul W.J., Cole J.R., Jesus E.C., Wang Q., Farris R., Fish J.A., Tiedje J.M. Bacterial community comparisons by taxonomy-supervised analysis independent of sequence alignment and clustering. PNAS USA, 2011, 108(35): 14637-14642. CrossRef 
9. Dol'nik A.S., Tamazyan G.S., Pershina E.V., Vyatkina K.V., Porozov Yu.B., Pinaev A.G., Andronov E.E. Sel’skokhozyaistvennaya Biologiya [Agricultural Biology], 2012, 5: 112-120.
10. Pershina E.V., Tamazyan G.S., Dol'nik A.S., Pinaev A.G., Sergaliev N.Kh., Andronov E.E. Ekologicheskaya genetika, 2012, 2: 31-38.
11. Andronov E.E., Petrova S.N., Chizhevskaya E.P., Korostik E.V., Akhtemova G.A., Pinaev A.G. Mikrobiologiya, 2009, 4(78): 525-534.
12. Weisburg W.G., Barns S.M., Pelletier D.A., Lane D.J. 16S ribosomal DNA amplification for phylogenetic study. J. Bacteriology, 1991, 2(173): 697-703.
13. Korostik E.V., Pinaev A.G., Andronov E.E. Ekologicheskaya genetika, 2006, 4: 32-37.
14. Singh B., Nazaries L., Munro S., Anderson I., Campbell C. Use of multiplex terminal restriction fragment length polymorphism for rapid and simultaneous analysis of different components of the soil microbial community. Appl. Environ. Microbiol., 2006, 72: 7278-7285. CrossRef 
15. Maniatis T., Frich E., Sembruk Dzh. Metody geneticheskoi inzhenerii. Molekulyarnoe klonirovanie [Methods of Genetic Engineering. Molecular Cloning]. Moscow, 1984.
16. Normand P., Orso S., Cournoyer B. Molecular phylogeny of the genus Frankia and related genera and emendation of the family Frankiaceae. J. Syst. Bacteriol., 1996, 46: 1-9. CrossRef 
17. Wang Q., Garrity G. M., Tiedje J. M., Cole J. R. Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol., 2007, 73(16): 5261-5267.
18. Bates S.T., Berg-Lyons D., Caporaso J.G., Walters W.A., Knight R., Fierer N. Examining the global distribution of dominant archaeal populations in soil.
ISME J., 2010, 5: 908-917. CrossRef 
19. Caporaso J.G., Kuczynski J., Stombaugh J., Bittinger K., Bush man F.D., Costello E.K., Fierer N., Peña A.G., Goodrich J.K., Gordon J.I., Huttley G.A., Kelley S.T., Knights D., Koenig J.E., Ley R.E., Lozupone C.A., McDonald D., Muegge B.D., Pirrung M., Reeder J., Sevinsky J.R., Turnbaugh P.J., Walters W.A., Widmann J., Yatsunen ko T., Zaneveld J., Knight R. QIIME allows analysis of high-throughput community sequencing data. Nature Methods, 2010, 7(5): 335-336. CrossRef 
20. Lozupone C.A., Knight R. Global patterns in bacterial diversity. PNAS USA, 2007, 27(104): 11436-11440. CrossRef 
21. Marchesi J.R., Sato T., Weightman A.J. Martin T.A., Fry J.C., Hiom S.J., Wade W.G. Design and evaluation of useful bacterium-specific PCR primers that amplify genes coding for bacterial 16S rRNA. Appl. Environ. Microbiol., 1998, 64: 795-799.

back