Comparison of Different Primer Sets for Use in Automated Ribosomal Intergenic Spacer Analysis of Complex Bacterial Communities

ITSF and ITSReub, constituting a new primer set designed for the amplification of the 16S-23S rRNA intergenic transcribed spacers, have been compared with primer sets consisting of 1406F and 23Sr (M. M. Fisher and E. W. Triplett, Appl. Environ. Microbiol. 65:4630-4636, 1999) and S-D-Bact-1522-b-S-20 and L-D-Bact-132-a-A-18 (L. Ranjard et al., Appl. Environ. Microbiol. 67:4479-4487, 2001), previously proposed for automated ribosomal intergenic spacer analysis (ARISA) of complex bacterial communities. An agricultural soil and a polluted soil, maize silage, goat milk, a small marble sample from the façade of the Certosa of Pavia (Pavia, Italy), and brine from a deep hypersaline anoxic basin in the Mediterranean Sea were analyzed with the three primer sets. The number of peaks in the ARISA profiles, the range of peak size (width of the profile), and the reproducibility of results were used as indices to evaluate the efficiency of the three primer sets. The overall data showed that ITSF and ITSReub generated the most informative (in term of peak number) and reproducible profiles and yielded a wider range of spacer sizes (134 to 1,387) than the other primer sets, which were limited in detecting long fragments. The minimum amount of DNA template and sensitivity in detection of minor DNA populations were evaluated with artificial mixtures of defined bacterial species. ITSF and ITSReub amplified all the bacteria at DNA template concentrations from 280 to 0.14 ng μl⁻¹, while the other primer sets failed to detect the spacers of one or more bacterial strains. Although the primer set consisting of ITSF and ITSReub and that of S-D-Bact-1522-b-S-20 and L-D-Bact-132-a-A-18 showed similar sensitivities for the DNA of Allorhizobium undicula mixed with the DNA of other species, the S-D-Bact-1522-b-S-20 and L-D-Bact-132-a-A-18 primer set failed to detect the DNA of Pseudomonas stutzeri.     

Influence of Commonly Used Primer Systems on Automated Ribosomal Intergenic Spacer Analysis of Bacterial Communities in Environmental Samples

Due to the high diversity of bacteria in many ecosystems, their slow generation times, specific but mostly unknown nutrient requirements and syntrophic interactions, isolation based approaches in microbial ecology mostly fail to describe microbial community structure. Thus, cultivation independent techniques, which rely on directly extracted nucleic acids from the environment, are a well-used alternative. For example, bacterial automated ribosomal intergenic spacer analysis (B-ARISA) is one of the widely used methods for fingerprinting bacterial communities after PCR-based amplification of selected regions of the operon coding for rRNA genes using community DNA. However, B-ARISA alone does not provide any taxonomic information and the results may be severely biased in relation to the primer set selection. Furthermore, amplified DNA stemming from mitochondrial or chloroplast templates might strongly bias the obtained fingerprints. In this study, we determined the applicability of three different B-ARISA primer sets to the study of bacterial communities. The results from in silico analysis harnessing publicly available sequence databases showed that all three primer sets tested are specific to bacteria but only two primers sets assure high bacterial taxa coverage (1406f/23Sr and ITSF/ITSReub). Considering the study of bacteria in a plant interface, the primer set ITSF/ITSReub was found to amplify (in silico) sequences of some important crop species such as Sorghum bicolor and Zea mays. Bacterial genera and plant species potentially amplified by different primer sets are given. These data were confirmed when DNA extracted from soil and plant samples were analyzed. The presented information could be useful when interpreting existing B-ARISA results and planning B-ARISA experiments, especially when plant DNA can be expected.     

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. Correspondence analysis revealed differences in community profiles generated by different primer sets, but overall ecological patterns were conserved in each case. ARISA is a powerful tool for evaluating BCC change through space and time, regardless of the specific primer set used.     

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. Correspondence analysis revealed differences in community profiles generated by different primer sets, but overall ecological patterns were conserved in each case. ARISA is a powerful tool for evaluating BCC change through space and time, regardless of the specific primer set used.     

Development of alternate ssu-rRNA probing strategies for characterizing aquatic microbial communities

Plastids in phytoplankton retain prokaryote-like DNA sequences that may generate false-positive signals from eubacterial small subunit (ssu) rRNA oligonucleotide probes, resulting in the overestimation of bacterial activity in aquatic microbial communities. To assess the extent of possible plastid-associated binding to eubacterial signals, we performed an extensive database search, flask experiments using algal and cyanobacterial pure cultures, and field trials on five common eubacterial probes: S-D-Bact-008-a-A-19, S-D-Bact-338-a-A-18, S-D-Bact-785-a-A-19, S-D-Bact-927-a-A-17, and S-D-Bact-1088-a-A-20. The database search and laboratory tests showed significant potential for binding among most bacterial probes and organelle ssu-rRNA. However, we propose two probing strategies to overcome this problem. First, one could use Bact-785 and Bact-338 in tandem, with the plastid component being estimated as the difference between the two signals (Bact-338 has approximately 70% overlap with known plastid sequences). Alternately, one might use Bact-338 as the primary eubacterial probe, but then use Cyan-785-a-A-19 (a probe that binds significantly to plastid rRNA) to correct for the plastid-associated false-positive signal. Both strategies would use a eukaryotic probe (S-D-Euca-1379-a-A-16) and Cyan-785-b-A-19 (a probe for most cyanobacteria) to further segregate rRNA signals. Trials were successfully performed using the strategies on samples from a recent field study.     

Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies

16S ribosomal RNA gene (rDNA) amplicon analysis remains the standard approach for the cultivation-independent investigation of microbial diversity. The accuracy of these analyses depends strongly on the choice of primers. The overall coverage and phylum spectrum of 175 primers and 512 primer pairs were evaluated in silico with respect to the SILVA 16S/18S rDNA non-redundant reference dataset (SSURef 108 NR). Based on this evaluation a selection of ‘best available’ primer pairs for Bacteria and Archaea for three amplicon size classes (100–400, 400–1000, ≥1000 bp) is provided. The most promising bacterial primer pair (S-D-Bact-0341-b-S-17/S-D-Bact-0785-a-A-21), with an amplicon size of 464 bp, was experimentally evaluated by comparing the taxonomic distribution of the 16S rDNA amplicons with 16S rDNA fragments from directly sequenced metagenomes. The results of this study may be used as a guideline for selecting primer pairs with the best overall coverage and phylum spectrum for specific applications, therefore reducing the bias in PCR-based microbial diversity studies.     

Combined eukaryotic and bacterial community fingerprinting of natural freshwater biofilms using automated ribosomal intergenic spacer analysis

Biofilms are complex communities playing an important role in aquatic ecosystems. Automated ribosomal intergenic spacer analysis (ARISA) has been used successfully to explore biofilm bacterial diversity. However, a gap remains to be filled as regards its application to biofilm eukaryotic populations. The aim of this study is to use ARISA to detect eukaryotic population shifts in biofilm. We designed a new set of primers to focus specifically on the ITS1-5.8S-ITS2 region of diatoms and tested it on natural biofilms. Additionally, we tested universal primers, used previously to perform ARISA on fungal communities. Cloning and sequencing showed that the universal primer set amplified various eukaryotes, whereas the new set was diatom specific. The new set amplified a wider variety of diatoms. Therefore, the universal set is appropriate to study the general eukaryotic population shifts in biofilms, whereas the new set is more appropriate to study diatoms specifically. We used both primer sets, along with a bacterial set, to study the population shifts in natural river biofilms. Principal component analysis of the ARISA fingerprints revealed seasonal shifts that did not coincide for bacterial and eukaryotic communities. Therefore, the use of both eukaryotic and bacterial primers provides a useful insight to assess microbial succession in biofilms.     

Automated approach for ribosomal intergenic spacer analysis of microbial diversity and its application to freshwater bacterial communities.

An automated method of ribosomal intergenic spacer analysis (ARISA) was developed for the rapid estimation of microbial diversity and community composition in freshwater environments. Following isolation of total community DNA, PCR amplification of the 16S-23S intergenic spacer region in the rRNA operon was performed with a fluorescence-labeled forward primer. ARISA-PCR fragments ranging in size from 400 to 1,200 bp were next discriminated and measured by using an automated electrophoresis system. Database information on the 16S-23S intergenic spacer was also examined, to understand the potential biases in diversity estimates provided by ARISA. In the analysis of three natural freshwater bacterial communities, ARISA was rapid and sensitive and provided highly reproducible community-specific profiles at all levels of replication tested. The ARISA profiles of the freshwater communities were quantitatively compared in terms of both their relative diversity and similarity level. The three communities had distinctly different profiles but were similar in their total number of fragments (range, 34 to 41). In addition, the pattern of major amplification products in representative profiles was not significantly altered when the PCR cycle number was reduced from 30 to 15, but the number of minor products (near the limit of detection) was sensitive to changes in cycling parameters. Overall, the results suggest that ARISA is a rapid and effective community analysis technique that can be used in conjunction with more accurate but labor-intensive methods (e.g., 16S rRNA gene cloning and sequencing) when fine-scale spatial and temporal resolution is needed.     

Automated Approach for Ribosomal Intergenic Spacer Analysis of Microbial Diversity and Its Application to Freshwater Bacterial Communities

An automated method of ribosomal intergenic spacer analysis (ARISA) was developed for the rapid estimation of microbial diversity and community composition in freshwater environments. Following isolation of total community DNA, PCR amplification of the 16S-23S intergenic spacer region in the rRNA operon was performed with a fluorescence-labeled forward primer. ARISA-PCR fragments ranging in size from 400 to 1,200 bp were next discriminated and measured by using an automated electrophoresis system. Database information on the 16S-23S intergenic spacer was also examined, to understand the potential biases in diversity estimates provided by ARISA. In the analysis of three natural freshwater bacterial communities, ARISA was rapid and sensitive and provided highly reproducible community-specific profiles at all levels of replication tested. The ARISA profiles of the freshwater communities were quantitatively compared in terms of both their relative diversity and similarity level. The three communities had distinctly different profiles but were similar in their total number of fragments (range, 34 to 41). In addition, the pattern of major amplification products in representative profiles was not significantly altered when the PCR cycle number was reduced from 30 to 15, but the number of minor products (near the limit of detection) was sensitive to changes in cycling parameters. Overall, the results suggest that ARISA is a rapid and effective community analysis technique that can be used in conjunction with more accurate but labor-intensive methods (e.g., 16S rRNA gene cloning and sequencing) when fine-scale spatial and temporal resolution is needed.     

Impact of catchment land use on bacterial communities within stream biofilms

The bacterial community structure in epilithic biofilms within 18 different streams was characterised using a community DNA fingerprinting technique (automated ribosomal intergenic spacer analysis—ARISA). Each stream has previously been described in terms of the dominant catchment land use, relative level of human disturbance and using a broad suite of water quality variables. Combination of ARISA with multivariate statistical analysis and ordination revealed that bacterial communities in streams located within rural catchments were significantly different to those within urban catchments. Broad-scale catchment land use described the largest component of the observed variation with no single water quality variable found to be a dominant determinant of the observed bacterial community variability, assessed using distance based redundancy analysis (dbRDA) of the ARISA data. This study highlights the potential of bacterial ARISA to provide a rapid and cost-effective approach to monitor the impact of catchment land use on aquatic ecosystems, such as the influence of encroaching urban development on the ecological health of rural streams.     

NESTED AUTOMATED RIBOSOMAL INTERGENIC SPACER ANALYSIS: A RAPID AND ACCURATE METHOD FOR COMPARISON OF BACTERIAL COMMUNITY COMPOSITION

Nested automated ribosomal intergenic spacer analysis (ARISA) was used to examine the community structure of epilithic biofilms in freshwater streams experiencing different levels of human impact. This molecular fingerprinting technique generated reproducible profiles of bacterial community structure that varied significantly between stream sites. Nested ARISA was determined to be a cost-effective, high-throughput approach to assess bacterial community composition from very small sample volumes, requiring little sampling effort and without the need for taxonomic identification of individual organisms. In combination with multidimensional scaling, nested ARISA provides a rapid and sensitive method to carry out complex analyses of bacterial community structure.

PRACTICAL APPLICATIONS

Nested automated ribosomal intergenic spacer analysis (ARISA) provides a high-throughput molecular method with which to screen large numbers of environmental samples for differences in microbial community structure. This sensitive approach benefits assessments from small sample volumes or environments exhibiting reduced microbial biomass (both aquatic and terrestrial). Differences in bacterial community structure (obtained from ARISA profiles) could be used to characterize the impact of anthropogenic disturbance on freshwater systems, analogous to the current use of macroinvertebrate indicators of freshwater ecological health.     

Differentiation of bacterial strains by thermal gradient gel electrophoresis using non-GC-clamped PCR primers for the 16S-23S rDNA intergenic spacer region

The method for DNA fingerprinting of the 16S-23S rDNA intergenic spacer region was modified to increase resolution of bacterial strains by thermal gradient gel electrophoresis (TGGE) analysis. By utilizing the high melting temperature region of the tRNA gene located in the middle of the 16S-23S rDNA intergenic spacer region as an internal clamp for TGGE, multiple melting domain problems were solved. PCR primers lacking a stretch of GC-rich sequences (GC-clamp) amplified the intergenic spacer region more efficiently than GC-clamped primers. Therefore, PCR artifacts were avoided by using low, 17-cycle, PCR. The method was successfully applied to diverse bacterial species for strain differentiation by TGGE without requiring a special PCR primer set.     

Comparison of Two Fingerprinting Techniques, Terminal Restriction Fragment Length Polymorphism and Automated Ribosomal Intergenic Spacer Analysis, for Determination of Bacterial Diversity in Aquatic Environments

We investigated bacterial diversity in different aquatic environments (including marine and lagoon sediments, coastal seawater, and groundwater), and we compared two fingerprinting techniques (terminal restriction fragment length polymorphism [T-RFLP] and automated ribosomal intergenic spacer analysis [ARISA]) which are currently utilized for estimating richness and community composition. Bacterial diversity ranged from 27 to 99 phylotypes (on average, 56) using the T-RFLP approach and from 62 to 101 genotypes (on average, 81) when the same samples were analyzed using ARISA. The total diversity encountered in all matrices analyzed was 144 phylotypes for T-RFLP and 200 genotypes for ARISA. Although the two techniques provided similar results in the analysis of community structure, bacterial richness and diversity estimates were significantly higher using ARISA. These findings suggest that ARISA is more effective than T-RFLP in detecting the presence of bacterial taxa accounting for <5% of total amplified product. ARISA enabled also distinction among aquatic bacterial isolates of Pseudomonas spp. which were indistinguishable using T-RFLP analysis. Overall, the results of this study show that ARISA is more accurate than T-RFLP analysis on the 16S rRNA gene for estimating the biodiversity of aquatic bacterial assemblages.     

Comparison of two fingerprinting techniques, terminal restriction fragment length polymorphism and automated ribosomal intergenic spacer analysis, for determination of bacterial diversity in aquatic environments

We investigated bacterial diversity in different aquatic environments (including marine and lagoon sediments, coastal seawater, and groundwater), and we compared two fingerprinting techniques (terminal restriction fragment length polymorphism [T-RFLP] and automated ribosomal intergenic spacer analysis [ARISA]) which are currently utilized for estimating richness and community composition. Bacterial diversity ranged from 27 to 99 phylotypes (on average, 56) using the T-RFLP approach and from 62 to 101 genotypes (on average, 81) when the same samples were analyzed using ARISA. The total diversity encountered in all matrices analyzed was 144 phylotypes for T-RFLP and 200 genotypes for ARISA. Although the two techniques provided similar results in the analysis of community structure, bacterial richness and diversity estimates were significantly higher using ARISA. These findings suggest that ARISA is more effective than T-RFLP in detecting the presence of bacterial taxa accounting for <5% of total amplified product. ARISA enabled also distinction among aquatic bacterial isolates of Pseudomonas spp. which were indistinguishable using T-RFLP analysis. Overall, the results of this study show that ARISA is more accurate than T-RFLP analysis on the 16S rRNA gene for estimating the biodiversity of aquatic bacterial assemblages.     

Culture-independent metagenomic approach to characterize the surface and subsurface soil bacterial community in the Brahmaputra valley,Assam, North-East India,an Indo-Burma mega-biodiversity hotspot

Soil bacterial communities, which contain the highest level of prokaryotic diversity of any natural environment, are important for ecosystem functioning. A culture-independent metagenomic approach was employed in the present investigation to characterize the diversity of soil bacterial community composition in five geochemically and hydrologically different surface and subsurface soil habitats of Brahmaputra valley, Assam, North-East India, an Indo-Burma mega-biodiversity hotspot. The diversity of soil bacterial community was determined through sequence analysis of 16S–23S intergenic spacer regions (ISR). Polymerase chain reaction (PCR) universal primers, 1406F (5′-TGYACACACCGCCCGT-3′) and 155r (5′-GGGTTBCATTCRG-3′) were used for amplification of 16S–23S ribosomal DNA intergenic spacers of bacteria. Amplification resulted in an intense array of PCR products approximately ranging in size from 200 to 900 bp. Clear banding patterns were observed in analysed samples using the primer set in combination. A clear change in microbial ISR profile was observed on visual analysis of gel electrophoresis profiles. Fast alignment database searches of PCR amplicons of 16S–23S ISR sequence data revealed that the isolated sequences resembled five major phylogenetic groups of bacteria, namely α-, β- and γ-subdivisions of Proteobacteria, Acidobacterium and Comamonadaceae.     

ribosort: a program for automated data preparation and exploratory analysis of microbial community fingerprints

ribosort is a computer package for convenient editing of automated ribosomal intergenic spacer analysis (ARISA) and terminal restriction fragment length polymorphism (TRFLP) data. It is designed to eliminate the labourious task of manually classifying community fingerprints in microbial ecology studies. This program automatically assigns detected fragments and their respective relative abundances to appropriate ribotypes. It permits simultaneous sorting of multiple profiles and facilitates direct workflow from TRFLP and ARISA output through to community analyses. ribosort also provides several options to merge repeat profiles of a sample into a single composite profile. By creating a 'ribotypes by samples' matrix ready for statistical analyses, use of the package saves time and simplifies the preparation of DNA fingerprint data sets for statistical analysis. In addition, ribosort performs exploratory analysis on the data by creating multidimensional scaling plots that compare the similarity of sample profiles using the statistical software r.     

Use of repetitive (repetitive extragenic palindromic and enterobacterial repetitive intergeneric consensus) sequences and the polymerase chain reaction to fingerprint the genomes of Rhizobium meliloti isolates and other soil bacteria.

The distribution of dispersed repetitive DNA (repetitive extragenic palindromic [REP] and enterobacterial repetitive intergenic consensus [ERIC]) sequences in the genomes of a number of gram-negative soil bacteria was examined by using conserved primers corresponding to REP and ERIC sequences and the polymerase chain reaction (PCR). The patterns of the resulting PCR products were analyzed on agarose gels and found to be highly specific for each strain. The REP and ERIC PCR patterns of a series of Rhizobium meliloti isolates, previously ordered in a phylogenetic tree based on allelic variations at 14 enzyme loci (B. D. Eardly, L. A. Materon, N. H. Smith, D. A. Johnson, M. D. Rumbaugh, and R. K. Selander, Appl. Environ. Microbiol. 56:187-194), were determined. Isolates which had been postulated to be closely related by multilocus enzyme electrophoresis also revealed similar REP and ERIC PCR patterns, suggesting that the REP and ERIC PCR method is useful for the identification and classification of bacterial strains.     

Bacterial communities associated with the rhizosphere of transgenic Bt 176 maize (Zea mays) and its non transgenic counterpart

The effect of transgenic Bt 176 maize on the rhizosphere bacterial community has been studied with a polyphasic approach by comparing the rhizosphere of Bt maize cultivated in greenhouse with that of its non transgenic counterpart grown in the same conditions. In the two plants the bacterial counts of the copiotrophic, oligotrophic and sporeforming bacteria, and the community level catabolic profiling, showed no significant differences; differences between the rhizosphere and bulk soil bacterial communities were evidenced. Automated ribosomal intergenic spacer analysis (ARISA) showed differences also in the rhizosphere communities at different plant ages, as well as between the two plant types. ARISA fingerprinting patterns of soil bacterial communities exposed to root growth solutions, collected from transgenic and non transgenic plants grown in hydroponic conditions, were grouped separately by principal component analysis suggesting that root exudates could determine the selection of different bacterial communities.     

Geographic and Environmental Sources of Variation in Lake Bacterial Community Composition

This study used a genetic fingerprinting technique (automated ribosomal intergenic spacer analysis [ARISA]) to characterize microbial communities from a culture-independent perspective and to identify those environmental factors that influence the diversity of bacterial assemblages in Wisconsin lakes. The relationships between bacterial community composition and 11 environmental variables for a suite of 30 lakes from northern and southern Wisconsin were explored by canonical correspondence analysis (CCA). In addition, the study assessed the influences of ARISA fragment detection threshold (sensitivity) and the quantitative, semiquantitative, and binary (presence-absence) use of ARISA data. It was determined that the sensitivity of ARISA was influential only when presence-absence-transformed data were used. The outcomes of analyses depended somewhat on the data transformation applied to ARISA data, but there were some features common to all of the CCA models. These commonalities indicated that differences in bacterial communities were best explained by regional (i.e., northern versus southern Wisconsin lakes) and landscape level (i.e., seepage lakes versus drainage lakes) factors. ARISA profiles from May samples were consistently different from those collected in other months. In addition, communities varied along gradients of pH and water clarity (Secchi depth) both within and among regions. The results demonstrate that environmental, temporal, regional, and landscape level features interact to determine the makeup of bacterial assemblages in northern temperate lakes.