Assessment of biases associated with profiling simple, model communities using terminal-restriction fragment length polymorphism-based analyses

Frey, Julie C.; Angert, Esther R.; Pell, Alice N.

doi:10.1016/j.mimet.2006.02.011

Cited by 37 publications

(36 citation statements)

References 41 publications

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“…This is largely dependent on how incomplete the DNA extraction from the sample is, and on biases in the target gene amplification. Earlier studies have addressed both factors, showed their overall importance, and identified the principle source of amplification bias, such as PCR primer discrimination against certain templates and/or inhibition of the more abundant templates' amplification by self-annealing (Suzuki and Giovannoni, 1996;Polz and cavanaugh, 1998;Webster et al, 2003;Acinas et al, 2004;Kurata et al, 2004;Frey et al, 2006;Sipos et al, 2007). This produces a qualitative picture of the overall importance of the PCR biases.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, existing DNA extraction protocols are not 100% efficient (Stach et al, 2001). It is well known that this skews the frequency distribution of rRNA gene species among the PCR products, in clone libraries, and in eventual sequence inventories (Tiedje, 1994;Suzuki and Giovannoni, 1996;Polz and Cavanaugh 1998;Acinas et al, 2004;Caron et al, 2004;Kurata et al, 2004;Frey et al, 2006;Sipos et al, 2007). What is not known is whether an increase in sequencing efforts, such as that afforded by the 454 Life Sciences sequencing technology (Sogin et al, 2006;Huber et al, 2007) would theoretically ensure a recovery of all rare rRNA species.…”

Section: Introductionmentioning

confidence: 99%

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Polymerase chain reaction primers miss half of rRNA microbial diversity

et al. 2009

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The rRNA approach is the principal tool to study microbial diversity, but it has important biases. These include polymerase chain reaction (PCR) primers bias, and relative inefficiency of DNA extraction techniques. Such sources of potential undersampling of microbial diversity are well known, but the scale of the undersampling has not been quantified. Using a marine tidal flat bacterial community as a model, we show that even with unlimited sampling and sequencing effort, a single combination of PCR primers/DNA extraction technique enables theoretical recovery of only half of the richness recoverable with three such combinations. This shows that different combinations of PCR primers/DNA extraction techniques recover in principle different species, as well as higher taxa. The majority of earlier estimates of microbial richness seem to be underestimates. The combined use of multiple PCR primer sets, multiple DNA extraction techniques, and deep community sequencing will minimize the biases and recover substantially more species than prior studies, but we caution that even this-yet to be used-approach may still leave an unknown number of species and higher taxa undetected.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Polymerase chain reaction primers miss half of rRNA microbial diversity

et al. 2009

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“…It is worth noting that this assumption is also tenuous due to complex interactions between taxa in ribosomal copy number, PCR bias, and DNA extraction bias (11). It is important to note that analysis of profiles by ordination is based on comparisons between rather than within samples and on the more realistic assumption that biases affecting taxa are the same across samples.…”

Section: Discussionmentioning

confidence: 99%

Interpreting Ecological Diversity Indices Applied to Terminal Restriction Fragment Length Polymorphism Data: Insights from Simulated Microbial Communities

Blackwood

Hudleston

Zak

et al. 2007

Appl Environ Microbiol

182

125

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Ecological diversity indices are frequently applied to molecular profiling methods, such as terminal restriction fragment length polymorphism (T-RFLP), in order to compare diversity among microbial communities. We performed simulations to determine whether diversity indices calculated from T-RFLP profiles could reflect the true diversity of the underlying communities despite potential analytical artifacts. These include multiple taxa generating the same terminal restriction fragment (TRF) and rare TRFs being excluded by a relative abundance (fluorescence) threshold. True community diversity was simulated using the lognormal species abundance distribution. Simulated T-RFLP profiles were generated by assigning each species a TRF size based on an empirical or modeled TRF size distribution. With a typical threshold (1%), the only consistently useful relationship was between Smith and Wilson evenness applied to T-RFLP data (TRF-E var ) and true Shannon diversity (H), with correlations between 0.71 and 0.81. TRF-H and true H were well correlated in the simulations using the lowest number of species, but this correlation declined substantially in simulations using greater numbers of species, to the point where TRF-H cannot be considered a useful statistic. The relationships between TRF diversity indices and true indices were sensitive to the relative abundance threshold, with greatly improved correlations observed using a 0.1% threshold, which was investigated for comparative purposes but is not possible to consistently achieve with current technology. In general, the use of diversity indices on T-RFLP data provides inaccurate estimates of true diversity in microbial communities (with the possible exception of TRF-E var ). We suggest that, where significant differences in T-RFLP diversity indices were found in previous work, these should be reinterpreted as a reflection of differences in community composition rather than a true difference in community diversity.

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“…However, it is generally accepted that the intersample variation in relative peak areas should not be affected by the biased PCR conditions because they similarly apply to all OTUs and samples (2,42). However, using peak areas as an indicator for absolute abundance has been confirmed to be a fruitless exercise, even when using simplified microbial communities (4,10,55). However, when experiments are performed under well-defined laboratory conditions or on simplified communities whose rrs copy numbers per genome are known, quantitative estimates of each target organism may be successfully obtained via community fingerprinting methods (27,41).…”

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confidence: 99%

Quantitative Community Fingerprinting Methods for Estimating the Abundance of Operational Taxonomic Units in Natural Microbial Communities

Ramette

2009

Appl Environ Microbiol

211

171

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Molecular fingerprinting techniques offer great promise for analyzing changes in microbial community structure, especially when dealing with large number of samples. However, a serious limitation has been the lack of quantification offered by such techniques since the relative abundances of the identified operational taxonomic units (OTUs) in the original samples are not measured. A quantitative fingerprinting approach designated "qfingerprinting" is proposed here. This method involves serial dilutions of the sample of interest and further systematic fingerprinting of all dilution series. Using the ultimate dilutions for which OTU are still PCR amplifiable and taking into account peak size inaccuracy and peak reproducibility, the relative abundance of each OTU is then simultaneously determined over a scale spanning several orders of magnitude. The approach was illustrated by using a quantitative version of automated ribosomal intergenic spacer analysis (ARISA), here called qARISA. After validating the concept with a synthetic mixture of known DNA targets, qfingerprinting was applied to well-studied marine sediment samples to examine specific changes in OTU abundance associated with sediment depth. The new strategy represents a major advance for the detailed quantitative description of specific OTUs within complex communities. Further ecological applications of the new strategy are also proposed.

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Assessment of biases associated with profiling simple, model communities using terminal-restriction fragment length polymorphism-based analyses

Cited by 37 publications

References 41 publications

Polymerase chain reaction primers miss half of rRNA microbial diversity

Polymerase chain reaction primers miss half of rRNA microbial diversity

Interpreting Ecological Diversity Indices Applied to Terminal Restriction Fragment Length Polymorphism Data: Insights from Simulated Microbial Communities

Quantitative Community Fingerprinting Methods for Estimating the Abundance of Operational Taxonomic Units in Natural Microbial Communities

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