A novel method to determine the minimum number of sequences required for reliable microbial community analysis

Journal of Microbiological Methods

Volumn 139, Issue , 2017, Pages 196-201

  Ni, Jiajia ^a,b,c,d   Li, Xiaojing ^a,b   He, Zhili ^e   Xu, Meiying ^a,b  

^a GUANGDONG INSTITUTE OF MICROBIOLOGY   (China)

^b State Key Laboratory of Oncologyin in South China   (China)

^c SOUTHERN MEDICAL UNIVERSITY   (China)

^d SOUTHERN MEDICAL UNIVERSITY   (China)

^e UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

Community structure; High throughput sequencing; Microbial community; Minimum number of sequences; Sequencing depth

Indexed keywords

RNA 16S;

16S RRNA GENE; ARTICLE; BIODEGRADABILITY; CONTROLLED STUDY; GENE SEQUENCE; HIGH THROUGHPUT SEQUENCING; MESOCOSM; MICROBIAL COMMUNITY; MICROBIAL DIVERSITY; MICROFLORA; NONHUMAN; POPULATION ABUNDANCE; PRIORITY JOURNAL; SEDIMENT; SPECIES DOMINANCE; BIOLOGY; COMPUTER SIMULATION; GENETICS; NUCLEOTIDE SEQUENCE; PHYLOGENY; PROCEDURES;

BASE SEQUENCE; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; MICROBIOTA; PHYLOGENY; RNA, RIBOSOMAL, 16S;

EID: 85020884537     PISSN: 01677012     EISSN: 18728359     Source Type: Journal    
DOI: 10.1016/j.mimet.2017.06.006     Document Type: Article

References (47)

1. Bartram, A.K., Lynch, M.D.J., Stearns, J.C., Moreno-Hagelsieb, G., Neufeld, J.D., Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end Illumina reads. Appl. Environ. Microbiol. 77 (2011), 3846–3852, 10.1128/AEM.02772-10.
2. Bik, E.M., Long, C.D., Armitage, G.C., Loomer, P., Emerson, J., Mongodin, E.F. et al., Bacterial diversity in the oral cavity of 10 healthy individuals. ISME J. 4 (2010), 962–974, 10.1038/ismej.2010.30.
3. Brose, U., Martinez, N.D., Williams, R.J., Estimating species richness: sensitivity to sample coverage and insensitivity to spatial patterns. Ecology 84 (2003), 2364–2377.
4. Campbell, B.J., Yu, L., Heidelberg, J.F., Kirchman, D.L., Activity of abundant and rare bacteria in a coastal ocean. Proc. Natl. Acad. Sci. U. S. A. 108 (2011), 12776–12781, 10.1073/pnas.1101405108.
5. Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K. et al., QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7 (2010), 335–336, 10.1038/nmeth.f.303.
6. Caporaso, J.G., Lauber, C.L., Walters, W.A., Berg-Lyons, D., Lozupone, C.A., Turnbaugh, P.J. et al., Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. U. S. A. 108 (2011), 4516–4522, 10.1073/pnas.1000080107.
7. Caporaso, J.G., Lauber, C.L., Walters, W.A., Berg-Lyons, D., Huntley, J., Fierer, N. et al., Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6 (2012), 1621–1624, 10.1038/ismej.2012.8.
8. Coveley, S., Elshahed, M.S., Youssef, N.H., Response of the rare biosphere to environmental disturbance in a highly diverse ecosystem (Zodletone spring, OK, USA). PeerJ, 3, 2015, e1182, 10.7717/peerj.1182.
9. Curtis, T.P., Sloan, W.T., Scannell, J.W., Estimating prokaryotic diversity and its limits. Proc. Natl. Acad. Sci. U. S. A. 99 (2002), 10494–10499.
10. Daniel, R., The metagenomics of soil. Nat. Rev. Microbiol. 3 (2005), 470–478.
11. Deng, C., Daley, T., Smith, A., Applications of species accumulation curves in large-scale biological data analysis. Quant. Biol. 3 (2015), 135–144, 10.1007/s40484-015-0049-7.
12. Deng, Y., He, Z., Xiong, J., Yu, H., Xu, M., Hobbie, S.E. et al., Elevated carbon dioxide accelerates the spatial turnover of soil microbial communities. Glob. Chang. Biol. 22 (2016), 957–964, 10.1111/gcb.13098.
13. Dixon, P., VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14 (2003), 927–930.
14. Dove, A.D.M., Cribb, T.H., Species accumulation curves and their applications in parasite ecology. Trends Parasitol. 22 (2006), 568–574.
15. Fang, Y., Xu, M., Chen, X., Sun, G., Guo, J., Wu, W. et al., Modified pretreatment method for total microbial DNA extraction from contaminated river sediment. Front. Environ. Sci. Eng. 9 (2015), 444–452, 10.1007/s11783-014-0679-4.
16. Gans, J., Wolinsky, M., Dunbar, J., Computational improvements reveal great bacterial diversity and high metal toxicity in soil. Science 309 (2005), 1387–1390.
17. Ge, Y., Schimel, J.P., Holden, P.A., Analysis of run-to-run variation of bar-coded pyrosequencing for evaluating bacterial community shifts and individual taxa dynamics. PLoS One, 9, 2014, e99414, 10.1371/journal.pone.0099414.
18. Gotelli, N.J., Colwell, R.K., Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4 (2001), 379–391.
19. Haegeman, B., Hamelin, J., Moriarty, J., Neal, P., Dushoff, J., Weitz, J.S., Robust estimation of microbial diversity in theory and in practice. ISME J. 7 (2013), 1092–1101, 10.1038/ismej.2013.10.
20. Harris, J.K., Sahl, J.W., Castoe, T.A., Wagner, B.D., Pollock, D.D., Spear, J.R., Comparison of normalization methods for construction of large, multiplex amplicon pools for next-generation sequencing. Appl. Environ. Microbiol. 76 (2010), 3863–3868, 10.1128/AEM.02585-09.
21. Horner-Devine, M.C., Carney, K.M., Bohannan, B.J.M., An ecological perspective on bacterial biodiversity. Proc. Biol. Sci. 271 (2004), 113–122.
22. Hortal, J., Borges, P.A.V., Gaspar, C., Evaluating the performance of species richness estimators: sensitivity to sample grain size. J. Anim. Ecol. 75 (2006), 274–287.
23. Hua, Z.S., Han, Y.J., Chen, L.X., Liu, J., Hu, M., Li, S.J. et al., Ecological roles of dominant and rare prokaryotes in acid mine drainage revealed by metagenomics and metatranscriptomics. ISME J. 9 (2015), 1280–1294, 10.1038/ismej.2014.212.
24. Hughes, J.B., Hellmann, J.J., Ricketts, T.H., Bohannan, B.J.M., Counting the uncountable: statistical approaches to estimating microbial diversity. Appl. Environ. Microbiol. 67 (2001), 4399–4406.
25. Huse, S.M., Dethlefsen, L., Huber, J.A., Mark Welch, D., Relman, D.A., Sogin, M.L., Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing. PLoS Genet., 4, 2008, e1000255, 10.1371/journal.pgen.1000255.
26. Kembel, S.W., Wu, M., Eisen, J.A., Green, J.L., Incorporating 16S gene copy number information improves estimates of microbial diversity and abundance. PLoS Comput. Biol., 8, 2012, e1002743, 10.1371/journal.pcbi.1002743.
27. Li, J., Ni, J., Li, J., Wang, C., Li, X., Wu, S. et al., Comparative study on gastrointestinal microbiota of eight fish species with different feeding habits. J. Appl. Microbiol. 117 (2014), 1750–1760, 10.1111/jam.12663.
28. Li, H., Qu, J., Li, T., Li, J., Lin, Q., Li, X., Pika population density is associated with the composition and diversity of gut microbiota. Front. Microbiol., 7, 2016, 758, 10.3389/fmicb.2016.00758.
29. Lundin, D., Severin, I., Logue, J.B., Östman, Ö., Andersson, A.F., Lindström, E.S., Which sequencing depth is sufficient to describe patterns in bacterial α- and β-diversity?. Environ. Microbiol. Rep. 4 (2012), 367–372, 10.1111/j.1758-2229.2012.00345.x.
30. Mao, C.X., Colwell, R.K., Chang, J., Estimating the species accumulation curve using mixtures. Biometrics 61 (2005), 433–441.
31. Martín, H.G., Goldenfeld, N., Estimation of microbial cover distributions at Mammoth Hot Springs using a multiple clone library resampling method. Environ. Microbiol. 8 (2006), 1145–1154.
32. Melo, A.S., Froehlich, C.G., Evaluation of methods for estimating macroinvertebrate species richness using individual stones in tropical streams. Freshw. Biol. 46 (2001), 711–721.
33. Metcalf, J.L., Xu, Z.Z., Weiss, S., Lax, S., Van Treuren, W., Hyde, E.R. et al., Microbial community assembly and metabolic function during mammalian corpse decomposition. Science 351 (2016), 158–162, 10.1126/science.aad2646.
34. Møller, A.K., Søborg, D.A., Al-Soud, W.A., Sørensen, S.J., Kroer, N., Bacterial community structure in high-arctic snow and freshwater as revealed by pyrosequencing of 16S rRNA genes and cultivation. Polar Res., 32, 2013, 17390, 10.3402/polar.v32i0.17390.
35. Mou, X., Jacob, J., Lu, X., Robbins, S., Sun, S., Ortiz, J.D. et al., Diversity and distribution of free-living and particle-associated bacterioplankton in Sandusky Bay and adjacent waters of Lake Erie Western Basin. J. Gt. Lakes Res. 39 (2013), 352–357, 10.1016/j.jglr.2013.03.014.
36. Ni, J., Xu, M., He, Z., Sun, G., Guo, J., Novel insight into evolutionary process from average genome size marine bacterioplanktonic biota. Appl. Ecol. Environ. Res. 14 (2016), 65–75, 10.15666/aeer/1402_065075.
37. Quince, C., Lanzen, A., Davenport, R.J., Turnbaugh, P.J., Removing noise from pyrosequenced amplicons. BMC Bioinf., 12, 2011, 38, 10.1186/1471-2105-12-38.
38. Roesch, L.F.W., Fulthorpe, R.R., Riva, A., Casella, G., Hadwin, A.K., Kent, A.D. et al., Pyrosequencing enumerates and contrasts soil microbial diversity. ISME J. 1 (2007), 283–290.
39. Techtmann, S.M., Fortney, J.L., Ayers, K.A., Joyner, D.C., Linley, T.D., Pfiffner, S.M. et al., The unique chemistry of eastern Mediterranean water masses selects for distinct microbial communities by depth. PLoS One, 10, 2015, e0120605, 10.1371/journal.pone.0120605.
40. Torsvik, V., Øvreås, L., Thingstad, T.F., Prokaryotic diversity - magnitude, dynamics, and controlling factors. Science 296 (2002), 1064–1066.
41. Tremblay, J., Singh, K., Fern, A., Kirton, E.S., He, S., Woyke, T. et al., Primer and platform effects on 16S rRNA tag sequencing. Front. Microbiol., 6, 2015, 771, 10.3389/fmicb.2015.00771.
42. Walther, B.A., Morand, S., Comparative performance of species richness estimation methods. Parasitology 116 (1998), 395–405.
43. Youssef, N., Sheik, C.S., Krumholz, L.R., Najar, F.Z., Roe, B.A., Elshahed, M.S., Comparison of species richness estimates obtained using nearly complete fragments and simulated pyrosequencing-generated fragments in 16S rRNA gene-based environmental surveys. Appl. Environ. Microbiol. 75 (2009), 5227–5236, 10.1128/AEM.00592-09.
44. Zhou, J., Wu, L., Deng, Y., Zhi, X., Jiang, Y.H., Tu, Q. et al., Reproducibility and quantitation of amplicon sequencing-based detection. ISME J. 5 (2011), 1303–1313, 10.1038/ismej.2011.11.
45. Zhou, J., Jiang, Y.H., Deng, Y., Shi, Z., Zhou, B.Y., Xue, K. et al., Random sampling process leads to overestimation of β-diversity of microbial communities. MBio, 4, 2013, e00324-13, 10.1128/mBio.00324-13.
46. Zhou, J., Deng, Y., Zhang, P., Xue, K., Liang, Y., Van Nostrand, J.D. et al., Stochasticity, succession, and environmental perturbations in a fluidic ecosystem. Proc. Natl. Acad. Sci. U. S. A. 111 (2014), E836–E845, 10.1073/pnas.1324044111.
47. Zhou, J., He, Z., Yang, Y., Deng, Y., Tringe, S.G., Alvarez-Cohen, L., High-throughput metagenomic technologies for complex microbial community analysis: open and closed formats. MBio, 6, 2015, e02288-14, 10.1128/mBio.02288-14.