Impact of T-RFLP data analysis choices on assessments of microbial community structure and dynamics

BMC Bioinformatics

Britt-Marie Wilén¹  Malte Hermansson³  Nils Johan Fredriksson² 

[1]Department of Civil and Environmental Engineering, Water Environment Technology, Chalmers University of Technology, Gothenburg, Sweden

[2]Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

[3]Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden

关键词: Bacterial community structure and dynamics;    Normalization;    Alignment;    Terminal restriction fragment polymorphism analysis;   

Others  :  1085212
DOI  :  10.1186/s12859-014-0360-8

 received in 2013-08-12, accepted in 2014-10-23,  发布年份 2014

【 摘 要 】

Background

Terminal restriction fragment length polymorphism (T-RFLP) analysis is a common DNA-fingerprinting technique used for comparisons of complex microbial communities. Although the technique is well established there is no consensus on how to treat T-RFLP data to achieve the highest possible accuracy and reproducibility. This study focused on two critical steps in the T-RFLP data treatment: the alignment of the terminal restriction fragments (T-RFs), which enables comparisons of samples, and the normalization of T-RF profiles, which adjusts for differences in signal strength, total fluorescence, between samples.

Results

Variations in the estimation of T-RF sizes were observed and these variations were found to affect the alignment of the T-RFs. A novel method was developed which improved the alignment by adjusting for systematic shifts in the T-RF size estimations between the T-RF profiles. Differences in total fluorescence were shown to be caused by differences in sample concentration and by the gel loading. Five normalization methods were evaluated and the total fluorescence normalization procedure based on peak height data was found to increase the similarity between replicate profiles the most. A high peak detection threshold, alignment correction, normalization and the use of consensus profiles instead of single profiles increased the similarity of replicate T-RF profiles, i.e. lead to an increased reproducibility. The impact of different treatment methods on the outcome of subsequent analyses of T-RFLP data was evaluated using a dataset from a longitudinal study of the bacterial community in an activated sludge wastewater treatment plant. Whether the alignment was corrected or not and if and how the T-RF profiles were normalized had a substantial impact on ordination analyses, assessments of bacterial dynamics and analyses of correlations with environmental parameters.

Conclusions

A novel method for the evaluation and correction of the alignment of T-RF profiles was shown to reduce the uncertainty and ambiguity in alignments of T-RF profiles. Large differences in the outcome of assessments of bacterial community structure and dynamics were observed between different alignment and normalization methods. The results of this study can therefore be of value when considering what methods to use in the analysis of T-RFLP data.

【 授权许可】

   
2014 Fredriksson et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]McMahon KD, Martin HG, Hugenholtz P: Integrating ecology into biotechnology. Curr Opin Biotechnol 2007, 18(3):287-292.
• [2]Bramucci M, Kane H, Chen M, Nagarajan V: Bacterial diversity in an industrial wastewater bioreactor. Appl Microbiol Biotechnol 2003, 62(5–6):594-600.
• [3]Schütte U, Abdo Z, Bent S, Shyu C, Williams C, Pierson J, Forney L: Advances in the use of terminal restriction fragment length polymorphism (T-RFLP) analysis of 16S rRNA genes to characterize microbial communities. Appl Microbiol Biotechnol 2008, 80(3):365-380.
• [4]Brugger SD, Frei L, Frey PM, Aebi S, Mühlemann K, Hilty M: 16S rRNA terminal restriction fragment length polymorphism for the characterization of the nasopharyngeal microbiota. PLoS One 2012, 7(12):e52241.
• [5]Hilty M, Qi W, Brugger SD, Frei L, Agyeman P, Frey PM, Aebi S, Mühlemann K: Nasopharyngeal microbiota in infants with acute otitis media. J Infect Dis 2012, 205(7):1048-1055.
• [6]Pilloni G, Granitsiotis MS, Engel M, Lueders T: Testing the limits of 454 Pyrotag sequencing: reproducibility, quantitative assessment and comparison to T-RFLP fingerprinting of aquifer microbes. PLoS One 2012, 7(7):e40467.
• [7]Cutler NA, Oliver AE, Viles HA, Ahmad S, Whiteley AS: The characterisation of eukaryotic microbial communities on sandstone buildings in Belfast, UK, using T-RFLP and 454 pyrosequencing. Int Biodeterioration Biodegradation 2013, 82:124-133.
• [8]Jakobsson HE, Jernberg C, Andersson AF, Sjölund-Karlsson M, Jansson JK, Engstrand L: Short-term antibiotic treatment has differing long-term impacts on the human throat and gut microbiome. PLoS One 2010, 5(3):e9836.
• [9]de la Fuente G, Belanche A, Girwood SE, Pinloche E, Wilkinson T, Newbold CJ: Pros and cons of ion-torrent next generation sequencing versus terminal restriction fragment length polymorphism T-RFLP for studying the rumen bacterial community. PLoS One 2014, 9(7):e101435.
• [10]Castro-Carrera T, Toral PG, Frutos P, McEwan NR, Hervás G, Abecia L, Pinloche E, Girdwood SE, Belenguer A: Rumen bacterial community evaluated by 454 pyrosequencing and terminal restriction fragment length polymorphism analyses in dairy sheep fed marine algae. J Dairy Sci 2014, 97(3):1661-1669.
• [11]Van Dorst J, Bissett A, Palmer AS, Brown M, Snape I, Stark JS, Raymond B, McKinlay J, Ji M, Winsley T, Ferrari BC: Community fingerprinting in a sequencing world. FEMS Microbiol Ecol 2014, 89(2):316-330.
• [12]Dunbar J, Ticknor LO, Kuske CR: Phylogenetic specificity and reproducibility and new method for analysis of terminal restriction fragment profiles of 16S rRNA genes from bacterial communities. Appl Environ Microbiol 2001, 67(1):190-197.
• [13]Culman SW, Gauch HG, Blackwood CB, Thies JE: Analysis of T-RFLP data using analysis of variance and ordination methods: a comparative study. J Microbiol Methods 2008, 75(1):55-63.
• [14]Smith CJ, Danilowicz BS, Clear AK, Costello FJ, Wilson B, Meijer WG: T-Align, a web-based tool for comparison of multiple terminal restriction fragment length polymorphism profiles. FEMS Microbiol Ecol 2005, 54(3):375-380.
• [15]Abdo Z, Schüette UM, Bent SJ, Williams CJ, Forney LJ, Joyce P: Statistical methods for characterizing diversity of microbial communities by analysis of terminal restriction fragment length polymorphisms of 16S rRNA genes. Environ Microbiol 2006, 8(5):929-938.
• [16]Culman S, Bukowski R, Gauch H, Cadillo-Quiroz H, Buckley D: T-REX: software for the processing and analysis of T-RFLP data. BMC Bioinformatics 2009, 10(1):171. BioMed Central Full Text
• [17]Kaplan CW, Astaire JC, Sanders ME, Reddy BS, Kitts CL: 16S ribosomal DNA terminal restriction fragment pattern analysis of bacterial communities in feces of rats fed lactobacillus acidophilus NCFM. Appl Environ Microbiol 2001, 67(4):1935-1939.
• [18]Sait L, Galic M, Strugnell RA, Janssen PH: Secretory antibodies do not affect the composition of the bacterial microbiota in the terminal ileum of 10-week-old mice. Appl Environ Microbiol 2003, 69(4):2100-2109.
• [19]Osborne CA, Rees GN, Bernstein Y, Janssen PH: New threshold and confidence estimates for terminal restriction fragment length polymorphism analysis of complex bacterial communities. Appl Environ Microbiol 2006, 72(2):1270-1278.
• [20]Kitts CL: Terminal restriction fragment patterns: a tool for comparing microbial communities and assessing community dynamics. Curr Issues Intest Microbiol 2001, 2(1):17-25.
• [21]Lueders T, Friedrich MW: Evaluation of PCR amplification bias by terminal restriction fragment length polymorphism analysis of small-subunit rRNA and mcrA genes by using defined template mixtures of methanogenic pure cultures and soil DNA extracts. Appl Environ Microbiol 2003, 69(1):320-326.
• [22]Li F, Hullar MAJ, Lampe JW: Optimization of terminal restriction fragment polymorphism (T-RFLP) analysis of human gut microbiota. J Microbiol Methods 2007, 68(2):303-311.
• [23]Bukovská P, Jelínková M, Hrselová H, Sýkorová Z, Gryndler M: Terminal restriction fragment length measurement errors are affected mainly by fragment length, G + C nucleotide content and secondary structure melting point. J Microbiol Methods 2010, 82(3):223-228.
• [24]Kaplan CW, Kitts CL: Variation between observed and true terminal restriction fragment length is dependent on true T-RF length and purine content. J Microbiol Methods 2003, 54(1):121-125.
• [25]Osborn AM, Moore ERB, Timmis KN: An evaluation of terminal-restriction fragment length polymorphism (T-RFLP) analysis for the study of microbial community structure and dynamics. Environ Microbiol 2000, 2:39-50.
• [26]Blackwood CB, Marsh T, Kim S-H, Paul EA: Terminal restriction fragment length polymorphism data analysis for quantitative comparison of microbial communities. Appl Environ Microbiol 2003, 69(2):926-932.
• [27]Rees G, Baldwin D, Watson G, Perryman S, Nielsen D: Ordination and significance testing of microbial community composition derived from terminal restriction fragment length polymorphisms: application of multivariate statistics. Antonie Van Leeuwenhoek 2004, 86(4):339-347.
• [28]Wilén B-M, Lumley D, Mattsson A, Mino T: Dynamics in flocculation and settling properties studied at a full-scale activated sludge plant. Water Environ Res 2010, 82(2):155-168.
• [29]Marchesi JR, Sato T, Weightman AJ, Martin TA, Fry JC, Hiom SJ, Wade WG: Design and evaluation of useful bacterium-specific PCR primers that amplify genes coding for bacterial 16S rRNA. Appl Environ Microbiol 1998, 64(2):795-799.
• [30]Fredriksson NJ, Hermansson M, Wilen B-M: The choice of PCR primers has great impact on assessments of bacterial community diversity and dynamics in a wastewater treatment plant. PLoS One 2013, 8(10):e76431.
• [31]Legendre P, Legendre L: Numerical Ecology. Elsevier Science BV, Amsterdam; 1998.