Use of direct gradient analysis to uncover biological hypotheses in 16s survey data and beyond

Scientific Reports

Volumn 2, Issue , 2012, Pages

  Erb Downward, John R ^a,e   Sadighi Akha, Amir A ^a   Wang, Juan ^c,e   Shen, Ning ^c,e   He, Bei ^c,e   Martinez, Fernando J ^a   Gyetko, Margaret R ^a,d,e   Curtis, Jeffrey L ^a,b,d,e   Huffnagle, Gary B ^a,b,e  

^a Division of Pulmonary and Critical Care Medicine   (United States)

^b UNIVERSITY OF MICHIGAN HEALTH SYSTEM   (United States)

^c PEKING UNIVERSITY   (China)

^d Pulmonary and Critical Care Medicine Section (506/111G)   (United States)

^e PEKING UNIVERSITY HEALTH SCIENCE CENTER   (China)

Author keywords

[No Author keywords available]

Indexed keywords

RNA 16S;

ANIMAL; ARTICLE; BACTERIUM; CECUM; GENETICS; HUMAN; LUNG; METABOLISM; METAGENOME; MICROBIOLOGY; MOUSE; PRINCIPAL COMPONENT ANALYSIS;

ANIMALS; BACTERIA; CECUM; HUMANS; LUNG; METAGENOME; MICE; PRINCIPAL COMPONENT ANALYSIS; RNA, RIBOSOMAL, 16S;

MLCS; MLOWN;

EID: 84872713677     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep00774     Document Type: Article

References (32)

1. Liu, Z., DeSantis, T. Z., Andersen, G. L. & Knight, R. Accurate taxonomy assignments from 16S rRNA sequences produced by highly parallel pyrosequencers. Nucleic Acids Res 36, e120 (2008
2. Schmidt, T. M. & Relman, D. A. Phylogenetic identification of uncultured pathogens using ribosomal RNA sequences. Methods Enzymol 235, 205-222 (1994).
3. Rothberg, J.M. & Leamon, J. H. The development and impact of 454 sequencing. Nat Biotechnol 26, 1117-1124 (2008).
4. Mason, K. L., Erb Downward, J. R., Falkowski, N. R., Young, V. B., Kao, J. Y. et al. Interplay between the Gastric Bacterial Microbiota and Candida albicans during Postantibiotic Recolonization and Gastritis. Infect Immun 80, 150-158 (2012).
5. Ramette, A. Multivariate analyses in microbial ecology. FEMS Microbiol Ecol 62, 142-160 (2007). (Pubitemid 47610610)
6. Turnbaugh, P. J. & Gordon, J. I. The core gut microbiome, energy balance and obesity. J Physiol 587, 4153-4158 (2009).
7. Turnbaugh, P. J., Ley, R. E., Mahowald,M. A., Magrini, V.,Mardis, E. R. et al. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444, 1027-1031 (2006). (Pubitemid 46018515)
8. Muegge, B. D., Kuczynski, J., Knights, D., Clemente, J. C., Gonzalez, A. et al. Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science 332, 970-974 (2011).
9. Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D. et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7, 335-336 (2010).
10. Lozupone, C. & Knight, R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71, 8228-8235 (2005). (Pubitemid 41803949)
11. Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M. et al. Introducingmothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75, 7537-7541 (2009).
12. Sun, Y., Cai, Y., Mai, V., Farmerie, W., Yu, F. et al. Advanced computational algorithms for microbial community analysis using massive 16S rRNA sequence data. Nucleic Acids Res 38, e205 (2010).
13. Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73, 5261-5267 (2007). (Pubitemid 47326658)
14. Minchin, P. R. An evaluation of relative robustness of techniques for ecological ordinations. Vegetatio 69, 89-107 (1987).
15. Legendre, P. & Legendre, L. Numerical Ecology. 853 (1998).
16. Erb-Downward, J. R., Thompson, D. L., Han, M. K., Freeman, C. M.,McCloskey, L. et al. Analysis of the lung microbiome in the "healthy" smoker and in COPD. PLoS One 6, e16384 (2011).
17. Ter Braak, C. J. F. Canonical Correspondence Analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology 67, 1167-1179 (1986).
18. Jari Oksanen, F., Guillaume Blanchet, Roeland Kindt, Pierre Legendre, R. B. O'Hara, et al. vegan: Community Ecology Package. R package version 1.17-3. 1.17-3 ed (2010).
19. Noverr, M. C., Noggle, R. M., Toews, G. B. & Huffnagle, G. B. Role of antibiotics and fungal microbiota in driving pulmonary allergic responses. Infect Immun 72, 4996-5003 (2004). (Pubitemid 39223382)
20. Mason, K. L., Erb Downward, J. R.,Mason, K. D., Falkowski, N. R., Eaton, K. A. et al. Candida albicans and Bacterial Microbiota Interactions in the Cecum during Recolonization following Broad-Spectrum Antibiotic Therapy. Infect Immun 80, 3371-3380 (2012).
21. Clarke, K. R. Non-parametric multivariate analyses of changes in community structure. Australian Journal of Ecology 18, 117-143 (1993). (Pubitemid 24409223)
22. Peres-Neto, P. & Jackson, D. How well do multivariate data sets match? The advantages of a Procrustean superimposition approach over the Mantel test. Oecologia 129, 169-178 (2001). (Pubitemid 32996560)
23. Mardia, K. V., Kent, J. T. & Bibby, J.M.Multivariate analysis: Academic Press (1979).
24. Zapala, M. A. & Schork, N. J. Multivariate regression analysis of distance matrices for testing associations between gene expression patterns and related variables. Proc Natl Acad Sci USA 103, 19430-19435 (2006). (Pubitemid 46026048)
25. Kuczynski, J., Liu, Z., Lozupone, C., McDonald, D., Fierer, N. et al. Microbial community resemblance methods differ in their ability to detect biologically relevant patterns. Nat Methods 7, 813-819 (2010).
26. Kosugi, Y., Sato, R., Genka, S., Shitara, N. & Takakura, K. An interactive multivariate analysis of FCM data. Cytometry 9, 405-408 (1988).
27. De Zen, L., Bicciato, S., te Kronnie, G.& Basso, G. Computational analysis of flowcytometry antigen expression profiles in childhood acute lymphoblastic leukemia: an MLL/AF4 identification. Leukemia 17, 1557-1565 (2003). (Pubitemid 36986958)
28. Lugli, E., Pinti, M., Nasi, M., Troiano, L., Ferraresi, R. et al. Subject classification obtained by cluster analysis and principal component analysis applied to flow cytometric data. Cytometry Part A 71A, 334-344 (2007). (Pubitemid 46717329)
29. Noverr, M. C., Falkowski, N. R., McDonald, R. A., McKenzie, A. N. & Huffnagle, G. B. Development of allergic airway disease in mice following antibiotic therapy and fungal microbiota increase: role of host genetics, antigen, and interleukin-13. Infect Immun 73, 30-38 (2005). (Pubitemid 40041094)
30. Hasegawa, M., Yamazaki, T., Kamada, N., Tawaratsumida, K., Kim, Y. G. et al. Nucleotide-binding oligomerization domain 1 mediates recognition of Clostridium difficile and induces neutrophil recruitment and protection against the pathogen. J Immunol 186, 4872-4880 (2011).
31. Hahne, F., LeMeur, N., Brinkman, R. R., Ellis, B., Haaland, P. et al. flowCore: a Bioconductor package for high throughput flow cytometry. BMC Bioinformatics 10, 106 (2009).
32. Murdoch, DAaD. rgl: 3D visualization device system (OpenGL). R package version 0.92.798 ed (2011).