Comparison of Primer Sets for Use in Automated Ribosomal Intergenic Spacer Analysis of Aquatic Bacterial Communities: an Ecological Perspective

Two primer sets for automated ribosomal intergenic spacer analysis(ARISA) were used to assess the bacterial community composition(BCC) in Lake Mendota, Wisconsin, over 3 years. Correspondenceanalysis revealed differences in community profiles generatedby different primer sets, but overall ecological patterns wereconserved in each case. ARISA is a powerful tool for evaluatingBCC change through space and time, regardless of the specificprimer set used.

INTRODUCTION

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Introduction

Studies conducted within an ecological framework often involvebroad-scale research questions whose answers depend less onobtaining a complete census of microbial populations than onthe ability to sample a system of interest with high spatialor temporal resolution. Current molecular microbial ecologymethods have allowed environmental microbiologists to ask importantecological questions that previously could not be addressedthrough culture-based approaches. Culture-independent methodsalso suffer from well-established limitations (7), however,and as such are useful but always imperfect. This is particularlytrue for PCR-based methods, since PCR amplification of microbialDNA can be subject to bias for a variety of reasons (10). Inspite of these limitations, great advances in the study of microbialecology have been made through the use of molecular methods.

A key component of any PCR-based method is the PCR primer set.Ideally, a universal primer set would amplify the target DNAfrom all taxonomic groups with equal efficiencies. No knownprimer sets meet this criterion. As a result, inconsistenciesin DNA amplification are likely to be observed between particularprimer sets.

The purpose of this study was to compare two recently evaluatedautomated ribosomal intergenic spacer analysis (ARISA) primersets (3) for use in aquatic microbial ecology. ARISA distinguishesmicrobial populations based on the length heterogeneity in theribosomal intergenic spacer region and provides a sensitiveanalysis of microbial communities at a relatively high levelof taxonomic resolution with significant reproducibility (3,6). In addition, the automated nature of the method enablesrapid analysis of a large number of samples collected over spaceor time. The efficacy of this method for ecological researchhas been demonstrated by our research group and others (8, 9,11). Here we sought to answer two important questions: (i) dodifferent ARISA primer sets provide dissimilar snapshots ofbacterial community composition (BCC), and (ii) do these primersets result in different conclusions about the ecology of anaquatic system?

Sampling and environmental data.

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Sampling and Environmental data.

Integrated water samples were taken from Lake Mendota (DaneCounty, WI) to a depth of 12 m approximately every 2 weeks duringthe ice-off season from April 2002 to October 2004. Microbialcommunities from 250 to 500 ml of lake water were captured on0.2-µm filters (Pall Life Sciences; catalog no. 63025).Filters were stored at –80°C until DNA was extractedusing a FastPrep DNA purification kit (Bio 101). Environmentaldata were collected by the North Temperate Lakes Long Term EcologicalResearch program (http://lter.limnology.wisc.edu). Completemethodology and data are available at http://lterquery.limnology.wisc.edu.

ARISA.

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Arisa.

ARISA was conducted on all samples using two primer sets. Primerset 1406f/23Sr consisted of 5'-TGYACACACCGCCCGT-3' (forwardprimer sequence) and 5'-GGGTTBCCCCATTCRG-3' (reverse primersequence). Primer set ITSF/ITSFReub consisted of 5'-GTCGTAACAAGGTAGCCGTA-3'(forward primer sequence) and 5'-GCCAAGGCATCCACC-3' (reverseprimer sequence). The conditions for ARISA PCR using the 1406f/23Srprimer set were described previously (9). ARISA PCR conditionsfor the ITSF/ITSReub primer set were previously described byCardinale et al. (3). Denaturing capillary electrophoresis wascarried out for each PCR using an ABI 3730 genetic analyzer(PE Biosystems) as described previously (9).

ARISA profiles were analyzed using a 100- to 2,000-bp custominternal size standard (Bioventures), Genescan 3.1.2 (AppliedBiosystems), and Genotyper 2.5 (Applied Biosystems), as describedby Kent et al. (9). To include the maximum number of peaks whileexcluding background fluorescence, a threshold of 50 fluorescenceunits greater than the baseline was used. Profiles obtainedwith each primer set were independently analyzed and comparedfor each sample. In addition, profiles generated using ITSF/ITSReubwere converted to the fragment length that would theoreticallybe detected using 1406f/23Sr by adding 197 base pairs and alignedusing Matlab 5.0 (The Mathworks). The 197-bp addition correspondsto the difference in length obtained by amplifying the 16S-23Sintergenic spacer region using primer set ITSF/ITSReub versusthat obtained with primer set 1406f/23Sr, based on Escherichiacoli numbering (1) (Fig. 1). This "converted" data set willbe referred to as cITSF/ITSReub.

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FIG. 1. The positions of the primers used in this study are shown on the prokaryotic rRNA operon. Bold lines indicate primer annealing sites using E. coli numbering. T, 1406f/23Sr primers utilized by Fisher and Triplett (6); C, ITSF/ITSReub primers introduced by Cardinale et al. (3); ITS, 16S-23S rRNA operon internal transcribed spacer. Length heterogeneity in the ITS sequence is used to distinguish microbial populations in ARISA. The 1406f/23Sr primer set amplifies an additional 197 bases compared to that amplified by the ITS/ITSReub primer set (based upon standard E. coli numbering). This value was added to ITSF/ITSReub data to generate the cITSF/ITSReub data set and allowed direct comparison of data produced from the two primer sets.

Multivariate statistical analyses.

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Multivariate statistical...

Correspondence analysis (CA) was carried out on the 1406f/23Sr,ITSF/ITSReub, and cITSF/ITSReub data sets. This approach isuseful for summarizing and graphically representing the multivariatedata collected over time and enables comparisons of ecologicalpatterns apparent in the data generated by each primer set.Samples with similar community structures plot close togetherin a CA ordination, and axes represent theoretical environmentalgradients, which can be compared to measured environmental variables.Axes were selected to explain the greatest variability in thecommunity data. CA biplots and correlation coefficients weregenerated using Canoco for Windows, version 4.51 (Biometris-PlantResearch International; 1997 to 2003).

Analysis of similarity (ANOSIM) is a method to test for differencesamong defined groups in multivariate data sets that is analogousto analysis of variance in univariate statistics (4). ANOSIMwas used to directly compare Lake Mendota BCC data producedby the 1406f/23Sr primer set with the cITSF/ITSReub profiles,testing the hypothesis that community profiles produced by thesame primer set are more similar to each other than to profilesproduced by different primer sets. Successive ANOSIM analyseswere conducted with the data set after peaks falling below athreshold of 1, 2, 3, 4, or 5% of total fluorescence were removed.ANOSIM produces a statistic, R, which indicates the magnitudeof difference among groups of samples. An R of 1 indicates thatthe communities completely differ among defined groups, andan R of 0 indicates no difference among groups (4, 5). The statisticalsignificance of R was tested by Monte Carlo randomization.

Profile composition.

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Profile composition.

BCC data generated by the two primer sets (1406f/23Sr and cITSF/ITSReub)were combined in a single correspondence analysis (Fig. 2).Samples amplified by the two primer sets strongly separate alongaxis 1 (Fig. 2A). The "primer" vector nearly parallel to axis1 illustrates the strong correlation between axis 1 and theprimer set used for ARISA (correlation coefficient, 0.975),indicating that the primer set best describes the differenceobserved among the samples despite correcting for the differencein amplicon length. These differences could be important atthe molecular and the methodological level and may significantlyinfluence conclusions about the presence of taxa or their relativeabundances.

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FIG. 2. Correspondence analyses biplots directly comparing ARISA data sets generated by using two different primer sets. Axes 1 and 2 (A) and axes 2 and 3 (B) of the ordination comparing 1406f/23Sr and converted ITSF/ITSReub ARISA data sets. Because of the length differences in the amplicons generated by the two primer sets, 197 bp was added to each fragment generated by ITSF/ITSReub PCR to allow direct comparison of community compositions by correspondence analysis. Filled symbols represent bacterial community data generated from ITSF/ITSReub ARISA, and open symbols represent community data generated using 1406f/23Sr. Squares, samples collected in spring and fall; circles, samples collected in summer. Vectors represent environmental variables and the dummy variable "PRIMER" (1, 1406f/23Sr; 0, ITSF/ITSReub). TP, total phosphorus; TEMP, water temperature; DRP, dissolved reactive phosphorus; NO2NO3, nitrite and nitrate.

To determine if the strong differences in BCC patterns due tothe primer set were driven by dominant or less-abundant populations(based upon relative areas of ARISA peaks), we gradually increasedthe minimum relative fluorescence threshold for inclusion inthe analysis. ANOSIM R values consistently decreased as thethreshold was increased from 0% (all peaks included) to 5% (onlydominant peaks included), indicating that when minor communitymembers are excluded the primer effect is reduced (Table 1).

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TABLE 1. ANOSIM R values for comparisons between ARISA profiles generated from primer set 1406f/23Sr and converted primer set ITSF/ITSReub

The observed differences between BCC determined using 1406f/23Srand ITSF/ITSReub appear to be driven largely by amplicons thatdo not contribute significantly to overall ARISA profile fluorescence.If we assume that relative fluorescence is proportional to relativeabundance (supported by (2), this observation could be the resultof differential amplification of rare taxa. If each primer setpreferentially amplifies different groups of rare taxa, thesimple conversion of the ITSF/ITSReub profiles to 1406f/23Srbins by adding 197 bp would generate dissimilar fingerprints,as we observe in Fig. 2A. Even if relative fluorescence is notcorrelated with relative abundance, the same subset of stronglyamplified taxa is represented in profiles generated by bothprimer sets. The ANOSIM sensitivity analysis (Table 1) demonstratesthat this subset of taxa dictates our interpretation of theLake Mendota bacterial community dynamics with either primerset.

Ecological conclusions and seasonal patterns.

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Ecological conclusions and...

Within the combined analysis, axes 2 and 3 of the CA ordinationcombine to best explain the variance in BCC driven by environmentalparameters and reveal substantial overlap between the two datasets (Fig. 2B). In addition, sample ordination along axes 2and 3 demonstrates good agreement between the 1406f/23Sr andcITSF/ITSReub data in seasonal separation and correlation withenvironmental variables. Individual CA ordinations of ARISAprofiles generated by each primer set show similar seasonalpatterns and relationships to chemical and physical variables(Fig. 3). The visual patterns in the ordinations are supportedby correlation coefficients between the axis 1 sample scoresfrom the independent correspondence analyses and environmentaldrivers that are shared among these data sets (Table 2). Thesigns and strengths of correlation were similar for bacterialcommunity data generated by each primer set.

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FIG. 3. Correspondence analysis biplots of bacterial community compositions in Lake Mendota. Seasonal dynamics of bacterioplankton communities were assessed from April 2002 to October 2004 using ARISA relative fluorescence values. ARISA data were generated with two different primer sets: (A) 1406f/23Sr (6) and (B) ITSF/ITSReub (3). Squares, samples collected in spring and fall; circles, samples collected in summer. Vectors represent environmental variables; the direction of increase for each variable and the length of each arrow indicate the degree of correlation with the ordination axes. TP, total phosphorus; TEMP, water temperature; DRP, dissolved reactive phosphorus; NH4, ammonium; NO2NO3, nitrite and nitrate.

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TABLE 2. Correlation coefficients between sample scores on the first ordination axis and environmental vectors calculated for community data generated by each primer set

The predominant ecological patterns in BCC were evident regardlessof the choice of primer set used for ARISA. Our two primer setslead to similar conclusions about seasonal patterns in BCC dynamicsin Lake Mendota over 3 years and the environmental factors thatdrive these patterns (Fig. 3).

A recent study evaluated three primer sets for use with ARISA,comparing the richnesses of ARISA profiles generated by eachprimer set from six environments (3). The results of this studyindicated dramatic differences in measured bacterial richnessamong the three primer sets, but we suggest that this methodof evaluation has limited ecological relevance, given the well-knownlimitations of molecular microbial ecology methods (7). Thepurpose of ARISA is not to evaluate richness and compositionof single samples. ARISA provides rapid, reproducible communityfingerprints that alone contain little information but, whenapplied in the context of an ecological question and comparedto other fingerprints through time or across space (9, 11),offer insight about drivers of community composition change.Our study suggests that different primer sets provide dissimilarfingerprints from a given environmental sample, likely due todifferential amplification of taxa with a small contributionto ARISA total fluorescence. However, when fingerprints fromdifferent primer sets are compared along some ecological gradient(time, space, etc.) the pattern of change inferred by ARISAis remarkably robust with respect to primer set.

ACKNOWLEDGMENTS

We thank Jed Fuhrman, Eric Triplett, and Ian Hewson for helpfuldiscussions and comments on the manuscript. We are also gratefulto the University of Wisconsin Center for Limnology and theNorth Temperate Lakes Long Term Ecological Research programfor environmental data and logistical support.

This research was supported in part by National Science FoundationMicrobial Observatories grant MCB-9977903 and by funding suppliedby the University of Wisconsin—Madison Graduate Schoolto K.D.M.

FOOTNOTES

* Corresponding author. Present address: Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801. Phone: (217) 333-4216. Fax: (217) 244-3219. E-mail: akent{at}uiuc.edu.

Published ahead of print on 22 November 2006.

REFERENCES

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