Evaluation of 16S rRNA amplicon sequencing using two next-generation sequencing technologies for phylogenetic analysis of the rumen bacterial community in steers

Journal of Microbiological Methods

Volumn 127, Issue , 2016, Pages 132-140

  Myer, Phillip R ^a   Kim, MinSeok ^b   Freetly, Harvey C ^b   Smith, Timothy P L ^b  

^a UNIVERSITY OF TENNESSEE   (United States)

^b U S MEAT ANIMAL RESEARCH CENTER   (United States)

Author keywords

16S rRNA gene; MiSeq; OTUs; PacBio; Rumen Microbiome

Indexed keywords

DNA FRAGMENT; RNA 16S; PRIMER DNA;

ACCURACY; AMPLICON; ARTICLE; BACTEROIDETES; BULLOCK; CONTROLLED STUDY; DNA LIBRARY; ECOLOGICAL NICHE; FIRMICUTES; GENE CLUSTER; GENE INSERTION; GENETIC DISTANCE; GENETIC SIMILARITY; GENETIC VARIABILITY; MALE; METAGENOMICS; MICROBIAL COMMUNITY; NEXT GENERATION SEQUENCING; NONHUMAN; PARAPREVOTELLACEAE; PHYLOGENY; POLYMERASE CHAIN REACTION; PREVOTELLA; PRIORITY JOURNAL; PROMOTER REGION; PROTEOBACTERIA; RNA SEQUENCE; RUMEN MICROORGANISM; SEQUENCE ANALYSIS; SUCCINICLASTICUM; SUCCINIVIBRIO; SUCCINIVIBRIONACEAE; TAXONOMY; VERRUCOMICROBIA; ANIMAL; BOVINE; DNA SEQUENCE; EVALUATION STUDY; GENETICS; HIGH THROUGHPUT SEQUENCING; MICROBIOLOGY; MICROFLORA; PROCEDURES; RUMEN;

ANIMALS; CATTLE; DNA PRIMERS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; MALE; MICROBIOTA; PHYLOGENY; RNA, RIBOSOMAL, 16S; RUMEN; SEQUENCE ANALYSIS, DNA;

EID: 84979266084     PISSN: 01677012     EISSN: 18728359     Source Type: Journal    
DOI: 10.1016/j.mimet.2016.06.004     Document Type: Article

References (48)

1. Aronesty, E., ea-utils : Command-line tools for processing biological sequencing data. http://code.google.com/p/ea-utils, 2011.
2. Baker, G.C., Smith, J.J., Cowan, D.A., Review and re-analysis of domain-specific 16S primers. J. Microbiol. Methods 55:3 (2003), 541–555.
3. Bath, C., Morrison, M., Ross, E.M., Hayes, B.J., Cocks, B.G., The symbiotic rumen microbiome and cattle performance: a brief review. Anim. Prod. Sci. 53 (2013), 876–881.
4. Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, 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., Yatsunenko, T., Zaneveld, J., Knight, R., Qiime allows analysis of high throughput community sequencing data. Nat. Methods 7 (2010), 335–336, 10.1038/nmeth.f.303.
5. Chakravorty, S., Helb, D., Burday, M., Connel, N., Alland, D., A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. J. Microbiol. Methods 69:2 (2007), 330–339.
6. Claesson, M.J., O'Sullivan, O., Wang, Q., Nikkila, J., Marchesi, J.R., Smidt, H., de Vos, W.M., Ross, R.P., O'Toole, P.W., Comparative analysis of pyrosequencing and a phylogenetic microarray for exploring microbial community structures in the human distal intestine. PLoS One, 4, 2009, e6669.
7. DeSantis, T.Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E.L., Keller, K., Huber, T., Dalevi, D., Hu, P., Andersen, G.L., Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB. Appl Environ Microbiol. 72 (2006), 5069–5072.
8. Edgar, R.C., Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:19 (2010), 2460–2461.
9. Fichot, E.B., Norman, S.R., Microbial phylogenetic profiling with the Pacific Biosciences sequencing platform. Microbiome, 1, 2013, 10.
10. Forney, L.J., Zhou, X., Brown, C.J., Molecular microbial ecology: land of the one-eyed king. Curr Opin Microbiol. 7 (2004), 210–220.
11. Giovannoni, S.J., Suzuki, M.T., Bias caused by template annealing in the amplification of mixtures of 16S rRNA genes by PCR. Appl. Environ. Microbiol. 62:2 (1996), 625–630.
12. Haas, B.J., Gevers, D., Earl, A.M., Feldgarden, M., Ward, D.V., Giannoukos, G., Ciulla, D., Tabbaa, D., Highlander, S.K., Sodergren, E., Methé, B., DeSantis, T.Z., The Human Microbiome Consortium, Petrosino, J.F., Knight, R., Birren, B.W., Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res. 21 (2011), 494–504.
13. Hamady, M., Knight, R., Microbial community profiling for human microbiome projects: Tools, techniques, and challenges. Genome Res. 19 (2009), 1141–1152.
14. Huse, S.M., Dethlefsen, L., Huber, J.A., Welch, D.M., Relman, D.A., Sogin, M.L., Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing. PLoS Genet., 4, 2008, e1000255.
15. Ibarbalz, F.M., Pérez, M.V., Figuerola, E.L.M., Erijman, L., The Bias Associated with Amplicon Sequencing Does Not Affect the Quantitative Assessment of Bacterial Community Dynamics. PLoS One, 9(6), 2014, e99722.
16. Jami, E., Mizrahi, I., Composition and Similarity of Bovine Rumen Microbiota across Individual Animals. PLoS ONE, 7(3), 2012, e33306.
17. Jami, E., White, B.A., Mizrahi, I., Potential Role of the Bovine Rumen Microbiome in Modulating Milk Composition and Feed Efficiency. PLoS One, 9(1), 2014, e85423.
18. Jumpstart Consortium Human Microbiome Project Data Generation Working Group, Evaluation of 16S rDNA-Based Community Profiling for Human Microbiome Research. PLoS One, 7(6), 2012, e39315.
19. Kang, S.H., Evans, P., Morrison, M., McSweeney, C., Identification of metabolically active proteobacterial and archaeal communities in the rumen by DNA- and RNA-derived 16S rRNA gene. J. Appl. Microbiol. 115 (2013), 644–653.
20. Kim, M., Morrison, M., Yu, Z., Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes. J Microbiol Methods. 84:1 (2011), 81–87.
21. Klindworth, A., Pruesse, E., Schweer, T., Peplies, J., Quast, C., Horn, M., Glockner, F.O., Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res., 41(1), 2013, e1.
22. Lane, D.J., 16S/23S rRNA sequencing. Stackebrandt, E., Goodfellow, M., (eds.) Nucleic acid techniques in bacterial systematics, 1991, John Wiley and Sons, New York, NY, 115–175.
23. Li, H., Zhang, Y., Li, D.S., Xu, H., Chen, G.X., Zhang, C.G., Comparisons of different hypervariable regions of rrs genes for fingerprinting of microbial communities in paddy soils. Soil Biol. Biochem. 41 (2009), 954–968.
24. 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, 2008, e120.
25. Liu, Z., Lozupone, C., Hamady, M., Bushman, F.D., Knight, R., Short pyrosequencing reads suffice for accurate microbial community analysis. Nucleic Acids Res., 35, 2007, 120.
26. Logares, R., Sunagawa, S., Salazar, G., Cornejo-Castillo, F.M., Ferrera, I., Sarmento, H., Hingamp, P., Ogata, H., de Vargas, C., Lima-Mendez, G., Raes, J., Poulain, J., Jaillon, O., Wincker, P., Kandels-Lewis, S., Karsenti, E., Bork, P., Acinas, S.G., Metagenomic 16S rDNA Illumina tags are a powerful alternative to amplicon sequencing to explore diversity and structure of microbial communities. Environ Microbiol. 16:9 (2014), 2659–2671.
27. Lozupone, C.A., Knight, R., Unifrac: A new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71 (2005), 8228–8235.
28. Martin, A., Phylogenetic approaches for describing and comparing the diversity of microbial communities. Appl. Environ. Microbiol. 68 (2002), 3673–3682.
29. McCann, J.C., Wiley, L.M., Forbes, T.D., Rouquette, F.M. Jr., Tedeschi, L.O., Relationship between the Rumen Microbiome and Residual Feed Intake-Efficiency of Brahman Bulls Stocked on Bermudagrass Pastures. PLoS ONE, 9(3), 2014, e91864.
30. de Menezes, A.B., Lewis, E., O'Donovan, M., O'Neill, B.F., Clipson, N., Doyle, E.M., Microbiome analysis of dairy cows fed pasture or total mixed ration diets. FEMS Microbiol. Ecol. 78:2 (2011), 256–265.
31. Myer, P.R., Smith, T.P.L., Wells, J.E., Kuehn, L.A., Freetly, H.C., Rumen microbiome from steers differing in feed efficiency. PLoS ONE, 10, 2015, e0129174, 10.1371/journal.pone.0129174.
32. Myer, P.R., Wells, J.E., Smith, T.P.L., Kuehn, L.A., Freetly, H.C., Cecum microbial communities from steers differing in feed efficiency. J. Anim. Sci. 93 (2015), 5327–5340, 10.2527/jas.2015-9415.
33. Myer, P.R., Wells, J.E., Smith, T.P.L., Kuehn, L.A., Freetly, H.C., Microbial community profiles of the colon from steers differing in feed efficiency. SpringerPlus 4:1 (2015), 1–13, 10.1186/s40064–015–1201-6.
34. Myer, P.R., Kim, M., Freetly, H.C., Smith, T.P.L., Analysis of metagenomic and near full-length 16S rRNA sequences to determine methods for phylogenetic analysis of the rumen bacterial community in steers. Data in Brief, 2016 (submitted for publication).
35. Myer, P.R., Wells, J.E., Smith, T.P.L., Kuehn, L.A., Freetly, H.C., Microbial community profiles of the jejunum from steers differing in feed efficiency. J. Anim. Sci. 94 (2016), 327–338, 10.2527/jas2015-9839.
36. Nossa, C.W., Oberdorf, W.E., Yang, L., Aas, J.A., Paster, B.J., Desantis, T.Z., et al. Design of 16S rRNA gene primers for454 pyrosequencing of the human foregut microbiome. World J. Gastroenterol. 16 (2010), 4135–4144.
37. Pinto, A.J., Raskin, L., PCR biases distort bacterial and archaeal community structure in pyrosequencing datasets. PLoS One, 7, 2012, e43093.
38. Pitta, D.W., Kumar, S., Vecchiarelli, B., Shirley, D.J., Bittinger, K., Baker, L.D., Ferguson, J.D., Thomsen, N., Temporal dynamics in the ruminal microbiome of dairy cows during the transition period. J. Anim. Sci. 92:9 (2014), 4014–4022.
39. Pitta, D., Pinchak, W., Dowd, S., Osterstock, J., Gontcharova, V., Rumen bacterial diversity dynamics associated with changing from bermudagrass hay to grazed winter wheat diets. Microb. Ecol. 59 (2010), 511–522.
40. Polz, M.F., Cavanaugh, C.M., Bias in Template-to-Product Ratios in Multitemplate PCR. Appl. Environ. Microbiol. 64:10 (1998), 3724–3730.
41. Price, M.N., Dehal, P.S., Arkin, A.P., FastTree 2 - Approximately maximum-likihood trees for large alignments. PLoS One, 5, 2010, E9490.
42. Ross, E.M., Moate, P.J., Bath, C.R., Davidson, S.E., Sawbridge, T.I., Guthridge, K.M., BG, C., Hayes, B.J., High throughput whole rumen metagenome profiling using untargeted massively parallel sequencing. BMC Genet., 13, 2012, 53.
43. Schloss, P.D., Westcott, S.L., Ryabin, T., et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75:23 (2009), 7537–7541, 10.1128/AEM.01541-09.
44. Stevenson, D.M., Weimer, P.J., Dominance of Prevotella and low abundance of classical ruminal bacterial species in the bovine rumen revealed by relative quantification real-time PCR. Appl. Microbiol. Biotechnol. 75:1 (2007), 165–174.
45. Turner, S., Pryer, K.M., Miao, V.P.W., Palmer, J.D., Investigating deep phylogenetic relationships among cyanobacteria and plastids by small subunit rRNA sequence analysis. J. Eukaryot. Microbiol. 46 (1999), 327–338.
46. Vinje, H., Liland, K.H., Almøy, T., Snipen, L., Comparing K-mer based methods for improved classification of 16S sequences. BMC Bioinf., 16(1), 2015, 205.
47. von Wintzingerode, F., Gobel, U.B., Stackebrandt, E., Determination of microbial diversity in environmental samples: pitfalls of PCR-based rRNA analysis. FEMS Microbiol. Rev. 21 (1997), 213–229.
48. Yu, Z., Morrison, M., Improved extraction of PCR-quality community DNA from digesta and fecal samples. Biotechniques 36:5 (2004), 808–813.