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Applied and Environmental Microbiology, December 2004, p. 7161-7172, Vol. 70, No. 12
0099-2240/04/$08.00+0     DOI: 10.1128/AEM.70.12.7161-7172.2004
Copyright © 2004, American Society for Microbiology. All Rights Reserved.

Development of a Universal Microarray Based on the Ligation Detection Reaction and 16S rRNA Gene Polymorphism To Target Diversity of Cyanobacteria

Bianca Castiglioni,1 Ermanno Rizzi,2 Andrea Frosini,3 Kaarina Sivonen,4 Pirjo Rajaniemi,4 Anne Rantala,4 Maria Angela Mugnai,5 Stefano Ventura,5 Annick Wilmotte,6 Christophe Boutte,6 Stana Grubisic,6 Pierre Balthasart,6 Clarissa Consolandi,3 Roberta Bordoni,2 Alessandra Mezzelani,2 Cristina Battaglia,3 and Gianluca De Bellis2*

Institute of Agricultural Biology and Biotechnology, Italian National Research Council, Milan,1 Institute of Biomedical Technologies, Italian National Research Council,2 Department of Biomedical Sciences and Technology, University of Milan, Segrate,3 Institute of Ecosystem Study, Section of Florence, Italian National Research Council, Sesto Fiorentino, Italy,5 Department of Applied Chemistry and Microbiology, Viikki Biocenter, University of Helsinki, Helsinki, Finland,4 Center for Protein Engineering, Institute of Chemistry, University of Liege, Liege, Belgium6

Received 6 April 2004/ Accepted 3 August 2004


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ABSTRACT
 
The cyanobacteria are photosynthetic prokaryotes of significant ecological and biotechnological interest, since they strongly contribute to primary production and are a rich source of bioactive compounds. In eutrophic fresh and brackish waters, their mass occurrences (water blooms) are often toxic and constitute a high potential risk for human health. Therefore, rapid and reliable identification of cyanobacterial species in complex environmental samples is important. Here we describe the development and validation of a microarray for the identification of cyanobacteria in aquatic environments. Our approach is based on the use of a ligation detection reaction coupled to a universal array. Probes were designed for detecting 19 cyanobacterial groups including Anabaena/Aphanizomenon, Calothrix, Cylindrospermopsis, Cylindrospermum, Gloeothece, halotolerants, Leptolyngbya, Palau Lyngbya, Microcystis, Nodularia, Nostoc, Planktothrix, Antarctic Phormidium, Prochlorococcus, Spirulina, Synechococcus, Synechocystis, Trichodesmium, and Woronichinia. These groups were identified based on an alignment of over 300 cyanobacterial 16S rRNA sequences. For validation of the microarrays, 95 samples (24 axenic strains from culture collections, 27 isolated strains, and 44 cloned fragments recovered from environmental samples) were tested. The results demonstrated a high discriminative power and sensitivity to 1 fmol of the PCR-amplified 16S rRNA gene. Accurate identification of target strains was also achieved with unbalanced mixes of PCR amplicons from different cyanobacteria and an environmental sample. Our universal array method shows great potential for rapid and reliable identification of cyanobacteria. It can be easily adapted to future development and could thus be applied both in research and environmental monitoring.


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INTRODUCTION
 
The cyanobacteria are photosynthetic prokaryotes that form a monophyletic group among the eubacteria (29). They are primary producers (3) and a rich source of bioactive compounds (1), and thus, they are ecologically and biotechnologically significant organisms. The cyanobacteria are distributed over a wide range of habitats. In eutrophic fresh and brackish waters, cyanobacteria frequently form toxic water blooms (23) that constitute high potential risks for animal and human health (13).

Traditionally, the identification of cyanobacteria has relied on morphological, physiological, and ecological characteristics that can vary under different environmental or growth conditions (3). Currently, the classification of cyanobacteria is based on a polyphasic approach that considers different phenotypic and genotypic features (29, 30). The molecular classification of cyanobacteria is based on 16S rRNA gene sequences obtained from pure cultures (30). Using this molecular information, several techniques can be employed to determine the cyanobacterial composition of an environmental sample. One of the most informative methods is based on amplification, cloning, sequencing, and phylogenetic reconstruction based on the entire 16S rRNA gene (8, 10). This strategy is very time-consuming and is therefore not suitable for large-scale screenings. Denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis have been widely applied to molecular ecological research (18). However, band excision, reamplification, and sequencing are necessary to identify community members.

Therefore, new approaches to the genetic analysis of complex cyanobacterial communities are needed. Recently, oligonucleotide microarrays (microchips) have been used widely in molecular biological studies and have shown great potential for environmental diagnostics. DNA microarray technology has already been applied for the detection of microbial diversity. Microarrays were used for analysis of cultured nitrifying bacteria (11) and for the direct detection of 16S rRNA in unpurified soil extracts (24), indicating their applicability for environmental studies. Loy and coworkers (15) and Wu and coworkers (32) tested the microarray method for actual environmental samples, the former for sulfate-reducing prokaryotes and the latter for functional genes of the nitrogen cycle. An oligonucleotide microarray method was also developed for the detection of 20 predominant human intestinal bacterial species (28). Wilson and coworkers (31) used a method based on Affymetrix GeneChip technology to study pure bacterial cultures.

The use of microarrays to specifically characterize cyanobacterial diversity is quite recent. Rudi and coworkers (21) designed a small cyanobacterium-specific microarray for the genera Microcystis, Planktothrix, Anabaena, Aphanizomenon, Nostoc, and Phormidium. Using this assay, the compositions of cyanobacteria in eight lake communities were determined. The DNA microarray and the magnetic-capture hybridization technique have been combined to form a new technology named MAG microarray. Bacterial magnetic particles on a MAG microarray were used for the identification of cyanobacterial DNA (17). Genus-specific oligonucleotide probes for the detection of Anabaena spp., Microcystis spp., Nostoc spp., Oscillatoria spp., and Synechococcus spp. have been designed from the variable region of the cyanobacterial 16S rRNA gene of 148 strains. All five cyanobacterial genera were successfully discriminated by using both axenic strains and unknown cultured cyanobacteria.

We applied a universal DNA array method to discriminate some groups of bacteria (2). This procedure is based on the discriminative properties of the DNA ligation detection reaction (LDR) and requires two probes specific for each target sequence, as described by Gerry et al. (7). A fluorescent label is coupled to one of the probes, and a complementary zip code (czip code) is coupled to the other. When the proper template is present, the two probes are ligated by the activity of a DNA ligase and are hybridized to the microarray spot that contains the corresponding zip code (Fig. 1). Such an array is called universal, because these zip code pairs could be used with any other probe set.



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  		FIG. 1. Main features of LDR method coupled with a universal microarray. After hybridization of a discriminating probe and a common probe to the target sequence (16S rRNA gene), ligation occurs only if there is perfect complementarity between the two probes and the template (A). The reaction is thermally cycled, generating single-stranded DNA fragments bearing a 5' Cy3 fluorescent moiety and a 3' czip code sequence. The cycling allows more common probe (and the corresponding czip code) to ligate to the discriminating probe, given a fixed amount of PCR target. (B) The LDR product is hybridized to a universal microarray, where unique zip code sequences have been spotted.

Here we present the universal DNA array method applied to the detection of cyanobacterial diversity. We designed probes specific for 19 different cyanobacterial groups identified from a phylogenetic tree built with the ARB program (16). The microarrays were validated with axenic and nonaxenic strains of cyanobacteria and an environmental sample.


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MATERIALS AND METHODS
 
All chemicals and solvents were purchased from Sigma-Aldrich (Milan, Italy) and used without further purification. The oligonucleotides were purchased from Thermo Electron GmbH (Ulm, Germany).

DNA samples.
The samples used to validate the probes included axenic strains kept in our culture collections, strains isolated from European lakes and a reservoir during this study (Table 1), and clones of environmental DNA libraries obtained from Lake Esch-sur-Sûre (Luxembourg) and Lake Tuusulanjärvi (Finland) (Table 2). The 16S rRNA gene of the cultured strains and clones was sequenced (unpublished data). In addition, the array was tested with an environmental DNA sample (Lake Tuusulanjärvi), which was isolated by the hot-phenol method (9). To verify the microarray results, the same environmental sample was analyzed by DGGE and cloning of the 16S rRNA gene.


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  		TABLE 1. Cyanobacterial strains used to validate the LDR procedure


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  		TABLE 2. Clones of 16S rRNA gene libraries obtained from environmental samples and used for validating the LDR

Ligation probe design.
For the LDR, we designed specific probes for the 16S rRNA gene sequences of 19 different cyanobacterial groups. These groups were identified by using a cyanobacterial 16S rRNA gene alignment built with ARB software, version Beta 011107 (16). The alignment contained 281 sequences from public databases and 57 from this study in addition to the out-group Escherichia coli. All of these sequences were longer than 1,400 bp, except the two sequences of Antarctic Phormidium (about 1,350 bp) and 21 (of 42) sequences of Prochlorococcus marinus (about 1,250 bp). All sequences were aligned with CLUSTAL W (26) and ARB. The sequence alignment is available upon request. The phylogenetic analysis was performed with ARB by using the neighbor-joining (NJ) algorithm (22). From the sequence alignment, group-specific consensus sequences were obtained with a cutoff percentage of 75%. If a base at a given position occurred at a lower frequency than the cutoff percentage, it was replaced by an appropriate International Union of Pure and Applied Chemistry ambiguity code in the consensus sequence. The group-specific consensus sequences were imported to GCG Omiga, version 2.0 (Oxford Molecular Ltd.), for group-specific probe design. The probes were designed by following the LDR approach. After hybridization of a discriminating probe and a common probe to the target sequence, ligation occurs only if there is perfect complementarity between the two probes and the template, in this case, an amplified fragment of the 16S rRNA gene (Fig. 1). For this reason, the discriminating probes were designed to have 3' ends unique to each of the 19 cyanobacterial groups. The common probes were located immediately after the discriminating probes according to the group-specific consensus sequences. An example of selection is shown in Fig. 2. To discard potentially unspecific probe pairs, we checked each probe pair (discriminating probe and common probe) by using the probe match tool of the ARB program. We also designed a probe pair (named UNICYANO) to detect the presence of any cyanobacteria in the sample. No significant self-annealing of the probe sequences was detected by computer analysis (data not shown). All probes were designed to have a theoretical melting temperature (Tm) between 63 and 68°C, calculated by using the Oligonucleotide Properties Calculator program (http://www.basic.nwu.edu/biotools/oligocalc.html).



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  		FIG. 2. Partial alignment of group-specific consensus sequences and an example of probe selection for Microcystis. The discriminating probe is indicated by light gray box, and the common probe is indicated by an unshaded box. The important base (A) at the 3' end of the discriminating probe is underlined.

We randomly selected 21 czip code sequences from those described by Gerry et al. (7) and Chen et al. (4). These czip codes were randomly assigned to the UNICYANO probe pair, the 19 group-specific probe pairs, and a positive control for the hybridization reaction. The latter was a Cy3-labeled czip code that has its own corresponding zip code in the universal array. As a negative control for the hybridization and LDR, double-distilled water was used instead of genomic DNA as the PCR template. The discriminating probes were labeled with Cy3 at the 5' end. The common probes were phosphorylated at the 5' end and carried the czip code at the 3' end. When a probe sequence contained an ambiguity code, this base was replaced with inosine during oligonucleotide synthesis.

Universal array preparation.
The microarrays were prepared by using CodeLink slides (Amersham Biosciences, Piscataway, N.J.), designed to covalently immobilize amino (NH2)-modified oligonucleotides. The 5' NH2-modified zip code oligonucleotides, carrying an additional poly(dA)10 tail at their 5' ends, were diluted to 25 µM in 100 mM phosphate buffer (pH 8.5). Spotting was performed by using a contact-dispensing system (MicroGrid II; BioRobotics, Huntingdon, United Kingdom). The printed slides were processed according to the manufacturer's protocols. Eight arrays per slide were generated. Quality control of the printed surfaces was performed by sampling one slide from each deposition batch. This slide was hybridized with 1 µM 5' Cy3-labeled poly(dT)10 in a solution containing 5x SSC (1x SSC is 0.15 M NaCl plus 0.015 M sodium citrate) and 0.1 mg of salmon sperm DNA/ml at room temperature for 2 h and then washed for 15 min in 1x SSC. The fluorescent signal was controlled by laser scanning, as described below.

PCR amplifications from DNA samples.
The 16S rRNA gene and the internal transcribed spacer region were amplified with universal primer 16S27F (5'-AGAGTTTGATCMTGGCTCAG-3') (6) and cyanobacterium-specific primer 23S30R (5'-CCTCGCCTCTGTGTGCCTAGGT-3') (14, 25). The PCR amplifications were performed with a GeneAmp PCR system 9700 thermal cycler (Applied Biosystems, Foster City, Calif.). The reaction mixtures included 500 nM concentrations of each primer, 200 µM concentrations of each deoxynucleoside triphosphate, 10 mM Tris-HCl (pH 8.8), 1.5 mM MgCl2, 50 mM KCl, 0.1% (wt/vol) Triton X-100, 1 U of DyNAzyme DNA polymerase II (Finnzymes, Espoo, Finland), and 5 to 8 ng of genomic DNA in a final volume of 50 µl. Prior to amplification, the DNA was denatured for 5 min at 95°C. Amplification consisted of 30 cycles at 94°C for 45 s, 57°C for 45 s, and 72°C for 2 min. After the cycles, an extension step (10 min at 72°C) was performed. The PCR products were purified by using a GFX PCR DNA purification kit (Amersham), eluted in 50 µl of autoclaved water, and quantified with a BioAnalyzer 2100 (Agilent Technologies, Palo Alto, Calif.).

LDR.
The LDR was carried out in a final volume of 20 µl containing 20 mM Tris-HCl (pH 7.5), 20 mM KCl, 10 mM MgCl2, 0.1% NP-40, 0.01 mM ATP, 1 mM dithiothreitol, 250 fmol of each discriminating probe, 250 fmol of each common probe, 10 fmol of the hybridization control, and from 0.5 to 100 fmol of purified PCR products. After the reaction mixture was preheated for 2 min at 94°C and centrifuged for 1 min, 4 U of Pfu DNA ligase (Stratagene, La Jolla, Calif.) was added. The LDR was cycled for 30 rounds at 90°C for 30 s and at 60°C for 4 min in a GeneAmp PCR system 9700 thermal cycler.

Array hybridization, detection, and data analysis.
The hybridization mixture had a total volume of 65 µl and contained 20 µl of LDR mixture, 5x SSC, and 0.1 mg of salmon sperm DNA/ml. After heating at 94°C for 2 min and chilling on ice, the hybridization mixture was applied to the slide, on which the eight arrays were separated by Press-To-Seal silicone isolators (1.0 x 9 mm; Schleicher & Schuell BioScience, Dassel, Germany). Hybridization was carried out in a chamber in the dark at 65°C for 1 h in a temperature-controlled water bath. After hybridization, the slide was washed at 65°C for 15 min in prewarmed 1x SSC and 0.1% sodium dodecyl sulfate. Finally, the slide was dried by spinning at 80 x g for 3 min. The fluorescent signals were acquired at a 5-µm resolution by using a ScanArray 4000 laser-scanning system (PerkinElmer Life and Analytical Sciences, Boston, Mass.) with a green laser for Cy3 dye ({lambda}ex, 543 nm; {lambda}em, 570 nm). Both the laser and the photomultiplier (PMT) tube power were set between 70 and 95%, depending on the signal intensities. QuantArray quantitative microarray analysis software (PerkinElmer) was used to quantitate the fluorescent intensity of the spots. The fluorescent intensity values obtained from the replicated spots (four replicate spots for each group-specific probe and eight replicates for the universal probe) and replicated experiment sets (three separate LDR-universal array experiments) were analyzed, and the means and standard deviations were calculated.

Concerning the method used to calculate nonspecific hybridization values, data analysis for each target was performed as follows: (i) the hybridization fluorescent intensities from nonspecific zip codes were calculated and averaged; (ii) the mean of these nonspecific hybridization values was compared with that of the expected positive zip code.


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RESULTS
 
Sequence analysis of cyanobacterial 16S rRNA genes and design of ligation probes.
The cyanobacterial groups identified with ARB by using the NJ alghorithm (as described in Materials and Methods) were named after the genus designations of their components: Anabaena/Aphanizomenon, Calothrix, Cylindrospermopsis, Cylindrospermum, Gloeothece, halotolerants, Leptolyngbya, Palau Lyngbya, Microcystis, Nodularia, Nostoc, Planktothrix, Antarctic Phormidium, P. marinus, Spirulina, Synechococcus, Synechocystis, Trichodesmium, and Woronichinia (Fig. 3). The list of strains present in each group is available at http://www.ulg.ac.be/cingprot/midichip/output/publications/Castiglioni_Tree.htm. For all of these, a group-specific consensus sequence was determined and used for probe design. The probes were designed to be complementary to the polymorphic regions of the group-specific consensus sequence alignment. We selected 19 group-specific probe pairs and a universal control probe matching all of the cyanobacteria. All of the probes had theoretical melting temperatures between 63 and 68°C. Table 3 lists all of the selected group-specific and universal probes and randomly chosen czip code sequences. Although DNA samples for some of the 19 selected groups (Gloeothece, Antarctic Phormidium, Trichodesmium, and Cylindrospermopsis) were not available, they were included to allow future applications of this cyanobacterial microarray.



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  		FIG. 3. NJ tree based on 16S rRNA gene sequences showing the 19 cyanobacterial groups. The probes used in the microarray were designed according to these groups. The P. marinus group is embedded in the large Synechococcus group. The tree contained 338 cyanobacterial 16S rRNA gene sequences. This phylogenetic tree stability has been supported by bootstrap analysis. For bootstrap analysis, 500 resamplings were performed by using the NJ algorithm in ARB. The bootstrap tree is available at http://www.ulg.ac.be/cingprot/midichip/output/publications/Castiglioni_Tree.htm.


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  		TABLE 3. List of group-specific probes and corresponding czip codes

Validation of universal array designed for cyanobacteria. (i) Specificity of probes.
In the presence of a proper DNA template, only group-specific spots, universal spots, and those spots corresponding to the hybridization control showed positive signals. Several examples of the results are shown in Fig. 4. The specificity of the probes for freshwater cyanobacterial groups was tested by using PCR-amplified 16S rRNA genes originating either from 52 cyanobacterial strains (both axenic and isolated in this study) or from 44 clones. Three replicated LDR-universal array experiments showed good reproducibility of the results.



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  		FIG. 4. Deposition scheme and several examples of LDR-universal array results. On the figure, the slide with eight arrays (top left corner), the deposition scheme of an array (top right corner), and a table specifying the cyanobacterial groups and the corresponding zip codes (bottom right corner) are shown. The hybridization-positive control is indicated by light gray shading, and the UNICYANO probe is indicated by boldface type. Each cyanobacterial group has four replicate spots. Hybridization results of the amplified 16S rRNA gene from the strains are shown in the bottom left corner. (A) Aphanizomenon sp. strain 202; (B) Calothrix sp. strain PCC 7714; (C) M. aeruginosa strain PCC 9354; (D) Plankthotrix sp. strain 1LT27S08; (E) S. major strain PCC 6313; (F) Synechococcus sp. strain Hegewald 74-30.

The intensities of signals of nonspecific hybridization for the cyanobacterial groups examined never exceeded 6% with respect to the expected positive signals (Table 4), and this value was used as the lower limit for positive signals in subsequent microarray analyses.


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  		TABLE 4. Evaluation of probe specificity and efficiency

To evaluate the relative ligation efficiency of the probes, the mean signal intensity values of the group-specific spots for each target were measured and normalized with respect to the signal intensity values of the universal spot. The hybridization intensities of the probes differed and ranged from 92 to 155% (Table 4).

A negative control of the entire process was performed by using double-distilled water instead of genomic DNA as the PCR template. Following hybridization on the universal chip, no signal was detected even after setting the PMT and laser to 95% power (data not shown).

(ii) LDR sensitivity.
To establish the detection limit of the method and the correlation between signal intensity and template concentration, we tested various template concentrations (0.5 to 100 fmol) in the LDR. The PCR products originated from the strains Planktothrix sp. strain 1LT27S08, Calothrix sp. strain PCC 7714, and Microcystis aeruginosa PCC 9354. The detected signals progressively decreased, and signal was detectable in up to 1 fmol of the PCR product, corresponding to 1 ng of amplified DNA. No signals were detected with 0.5 fmol of the PCR product, even after setting the PMT and laser to 95% power (data not shown). We found a linear correlation (R2 = 0.98, 0.94, and 0.96, respectively) between signal intensity and template concentration (Fig. 5A). Nevertheless, the signal-to-noise ratio also decreased with gradually reducing template concentration (Fig. 5B). This ratio was obtained from the signal intensities of the target-specific spots divided by the mean signal intensity of the nonspecific spots. The signal-to-noise ratio was clearly higher at template quantities above 25 fmol than at lower quantities (Fig. 5B). Essentially the same results were obtained with similar concentrations of PCR products derived from Calothrix sp. strain PCC 7714 and M. aeruginosa PCC 9354 as the LDR substrate (data not shown). Therefore, the target concentration of 25 fmol of each strain or clone was used in the LDR.



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  		FIG. 5. Testing of LDR sensitivity. (A) Correlation between signal intensity and template concentration. The effect of template concentration on LDR was tested with PCR products of Planktothrix sp. strain 1LT27S08, Calothrix sp. strain PCC 7714, and M. aeruginosa strain PCC 9354, ranging from 0.5 to 100 fmol. (B) Signal-to-noise ratio plotted against template quantity. Each data point represents the ratio between the mean signal intensity of the target-specific zip codes and the mean signal intensity of nonspecific zip codes. PCR products from Planktothrix sp. strain 1LT27S08 (1 to 100 fmol) were used as a template. The signal-to-noise ratio increases with growing template concentrations.

Use of artificial mixes of PCR products from different strains.
To determine the efficiency of the LDR method in the presence of complex molecular targets, we used artificial mixes with unequal amounts of PCR products derived from the following cyanobacterial strains: M. aeruginosa PCC 9354, Aphanizomenon sp. strain 202, Planktothrix sp. strain 1LT27S08, Spirulina major sp. strain PCC 6313, and Calothrix sp. strain PCC 7714. After separate PCRs, the amplified fragments were pooled in the unbalanced mixes. In all of these experiments, the unbalanced mixes were 5 fmol of both S. major and Calothrix versus 100 fmol of both Aphanizomenon and Microcystis or Planktothrix. After hybridization of the LDR products on the universal array, all of the expected signals were detected and easily discriminated from the nonspecific signals. An example of these experiments is shown in Fig. 6A. The amplicon concentrations were reflected in the signal intensities (Fig. 6A).



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  		FIG. 6. Microarray analyses of complex cyanobacterial samples. (A) The hybridization result of the unbalanced LDR mix shows how spot intensity (left) and measured fluorescence intensity (right) correspond to the concentrations of targets. The LDR mix contained 100 fmol of the PCR product from both M. aeruginosa strain PCC 9354 and Aphanizomenon sp. strain 202 and 5 fmol of the PCR product of both S. major strain PCC 6313 and Calothrix sp. strain PCC 7714. (B) The environmental sample 0TU27 from Lake Tuusulanjärvi (Finland) was analyzed with the array. The hybridization pattern shows the presence of Microcystis, Anabaena/Aphanizomenon, and Woronichinia spp.

LDR detection on universal array of the 16S rRNA gene from an environmental sample.
The 16S rRNA gene from a sample collected from Lake Tuusulanjärvi was analyzed to evaluate the DNA microarray applicability for environmental studies. Microarray hybridization patterns showed the presence of Microcystis, Anabaena/Aphanizomenon, and Woronichinia spp. (Fig. 6B). In DGGE, the following cyanobacterial groups were detected: Microcystis, Snowella, and Anabaena/Aphanizomenon. Cloning revealed the following groups: Microcystis (the most abundant group, 62% of the cyanobacterial clones), Anabaena/Aphanizomenon (18%), and Snowella (15%) (A. Rantala, P. Rajaniemi, and K. Sivonen, unpublished data).


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DISCUSSION
 
Studies in environmental microbiology are often limited by difficulties in identifying the diversity of natural populations because isolation and cultivation of microorganisms from natural environments are sometimes impossible. Molecular approaches are intended to overcome this problem. We designed and tested a microarray-based method for detection of cyanobacterial diversity. The method was based on our previous experience with a bacterial universal array (2). In that study, we developed and evaluated a molecular strategy based on amplification of the cyanobacterial 16S rRNA gene region and its molecular discrimination with the LDR-universal array approach. Using the universal array, we overcame one of the major limitations of DNA microarray approaches based on hybridization. Optimal hybridization conditions are difficult to determine for large sets of different probes, which need to be hybridized on a DNA chip at the same time (15, 21). In the universal array-based approach, the optimization of hybridization conditions for each probe set is not required. New probe pairs can be added to the array without further optimization, thus reducing costs and setup time. Furthermore, problems due to secondary structures of the target DNA or steric hindrances of differently sized nucleic acid hybrids formed on the microarrays after hybridization (20) are minimized. However, this method requires an extra step (the ligation) with respect to DNA microarray approaches based on hybridization.

In the present study, all of the LDR probes selected were designed to have high theoretical melting temperatures to perform the ligation reaction at 60°C, which prevented problems caused by secondary structures of the target DNA. Additionally, the ligated products were sterically similar. In the LDR, the specificity of the hybridization probes and the selectivity of the ligation reaction are combined to increase the discrimination power. Furthermore, with the LDR it is possible to target several PCR amplicons at the same time in a single ligation reaction (multiplexing).

As described by Consolandi et al. (5), up to 54 different discriminating probes can be used in such a multiplex ligation reaction without affecting the efficiency of the method.

We employed semi-cyanobacterium-specific PCR primers, 16S27F-23S30R (14, 25), instead of the universal primer pair, 16S27F-16S1492R (6), to eliminate the diversity of microorganisms other than cyanobacteria. The use of more specific cyanobacterial primers, such as CYA359F and CYA781R (19), which amplify only about 400 bp, would have limited the phylogenetic resolution.

We designed the probes based on a large number of cyanobacterial sequences (338) covering 19 major groups of planktonic cyanobacteria, which is more than in previous studies (17, 21). To allow for wider applicability of the array in future diversity studies, we also included groups not present in lakes, such as Trichodesmium.

Probe design can be considered a crucial point in the LDR approach. During definition of the group-specific consensus sequences, we set the cutoff value to preserve as much sequence information as possible. This sometimes required the inclusion of some degenerated positions in the probe sequences. A maximum of two inosine residues was included per probe (Table 3).

We evaluated our array by testing 95 samples of known 16S rRNA gene sequences: 51 strains belonging to 14 phylogenetic lineages and 44 cloned fragments from lake samples. We found perfect correspondence between the expected and actual LDR results. In fact, all samples yielded the positive signals expected without ambiguity. Nonspecific signals were always below 6% of the total signal intensities. This excellent selectivity is needed for testing complex environmental samples.

The relative probe efficiency was determined by normalizing all specific signals to the corresponding universal cyanobacterial probe. The normalized signal ranged from 92% (Leptolyngbya) to 155% (Microcystis), demonstrating a sufficient level of uniformity in the performance of the array.

Although the probes have theoretical melting temperatures varying by 5°C, this variation does not seem to be related to the relative probe efficiency.

The sensitivity of the method was investigated by using different concentrations of target DNA (amplicon of Planktothrix sp. strain 1LT27S08). The log plot of the signal intensity versus the total amount of amplicon showed a good linear relationship (Fig. 5). Similar results were obtained with amplicons from two other strains. The efficiency of the LDR method in the presence of complex molecular targets was assessed by means of artificial mixes composed of unbalanced amounts (100:5 fmol) of PCR products. All of the signals expected were detected and easily discriminated from nonspecific signals, indicating that a reasonable association can be found between the composition of the sample and the LDR-universal array signals. However, it should be noted that the PCR is known to introduce bias (27); therefore, caution should be taken when assuming the results of PCR-LDR-universal array as quantitative indicators of the original sample composition.

Finally, we evaluated this method by using an environmental sample; the microarray hybridization pattern showed the presence of Microcystis, Anabaena/Aphanizomenon, and Woronichinia spp. These results were compared with those of light microscopy (morphotypes) (L. Lepistö and P. Kuuppo, unpublished data) as well as cloning and DGGE analyses of the same environmental sample (unpublished results). Consistent with the microarray results, the presence of Microcystis and Anabaena/Aphanizomenon spp. was detected. In addition, the DGGE results showed the presence of Snowella but did not detect Woronichinia spp. This discrepancy in results can be discussed considering that the genera Snowella and Woronichinia belong to the subfamily Gomphosphaerioideae according to traditional botanic taxonomy (12); up to now, sequences of strains belonging to this subfamily have not been published. Recently, strains of genus Snowella were successfully isolated and characterized phylogenetically based on the 16S rRNA gene sequences (P. Rajaniemi, M. A. Mugnai, A. Rantala, S. Turicchia, S. Ventura, J. Komarkova, L. Lepistö, and K. Sivonen, unpublished data). The Snowella strains formed a highly supported cluster with the Woronichinia strains in all phylogenetic analyses of the 16S rRNA gene sequences. So it is possible that DGGE and microarray detect the same genotype that, lacking additional information, has been called Woronichinia on the basis of the only two Woronichinia sequences obtained during this work, which should be considered Snowella based on these unpublished new data.

In conclusion, we demonstrated the feasibility of the universal array-based approach, combined with the LDR for the identification of cyanobacteria. The method we established is specific, yielding unequivocal identification of the cyanobacteria, sensitive (down to 1 fmol can be detected), and amenable to the analysis of complex environmental samples. This method has wide potential for the monitoring of cyanobacteria, e.g., by water authorities and companies. This technology can be easily applied to the future study of other marker genes, one of the most interesting of which would be the combination of the array developed here with one that could detect potentially toxic cyanobacteria. This would reveal the genetic diversity of cyanobacteria as well as the presence of potentially toxic genotypes in a sample.


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ACKNOWLEDGMENTS
 
This work was performed as part of the MIDI-CHIP project (www.ulg.ac.be/cingprot/midichip/index.htm) funded by the European Union (contract EVK2-CT-1999-00026).

Several partners of the MIDI-CHIP project are acknowledged for sharing their samples and expertise. We are grateful to E. Hegewald and N. Jeeji-Bai (Forschungszentrum Jülich, Jülich, Germany) and D. J. Scanlan (University of Warwick, Warwick, United Kingdom) for DNA samples of their strains.


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FOOTNOTES
 
* Corresponding author. Mailing address: Istituto di Tecnologie Biomediche, Consiglio Nazionale delle Ricerche, Via Cervi 93, 20090 Segrate (Mi), Italy. Phone: 39 02 26422764. Fax: 39 02 26422770. E-mail: gianluca.debellis{at}itb.cnr.it. Back


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Applied and Environmental Microbiology, December 2004, p. 7161-7172, Vol. 70, No. 12
0099-2240/04/$08.00+0     DOI: 10.1128/AEM.70.12.7161-7172.2004
Copyright © 2004, American Society for Microbiology. All Rights Reserved.



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