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Keywords:

  • arbuscular mycorrhizal (AM) fungi;
  • Candidatus Glomeribacter gigasporarum;
  • endobacteria;
  • Gigaspora margarita;
  • microbial detection and quantification;
  • real-time quantitative polymerase chain reaction (qPCR);
  • single-copy genes

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  • • 
    A combined approach based on quantitative and nested polymerase chain reaction (qPCR and nPCR, respectively) has been set up to detect and quantify the unculturable endobacterium Candidatus Glomeribacter gigasporarum inside the spores of its fungal host Gigaspora margarita.
  • • 
    Four genes were targeted, two of bacterial origin (23S rRNA gene and rpoB) and two from the fungus (18S rRNA gene and EF1-α).
  • • 
    The sensitivity of the qPCR protocol has proved to be comparable to that of nPCR, both for the fungal and the bacterial detection. It has been demonstrated that the last detected dilution in qPCR corresponded, in each case, to 10 copies of the target sequences, suggesting that the method is equally sensitive for the detection of both fungal and bacterial targets. As the two targeted bacterial genes are predicted to be in single copy, it can be concluded that the detection limit is of 10 bacterial genomes for each mixture. The protocol was then successfully applied to amplify fungal and bacterial DNA from auxiliary cells and extraradical and intraradical mycelium.
  • • 
    For the first time qPCR has been applied to a complex biological system to detect and quantify fungal and bacterial components using single-copy genes, and to monitor the bacterial presence throughout the fungal life cycle.

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Nucleic acid-targeted analyses, and especially polymerase chain reaction (PCR)-based techniques, are widely used for microbial detection and quantification, mainly because of their ability to detect DNA at low concentrations. Quantitative real-time PCR (qPCR) has recently emerged for the detection and quantification of microorganisms. Because it is a very powerful, cultivation-independent, rapid and sensitive method, qPCR has been used for the detection of various organisms in a wide range of research fields. For example, qPCR has so far been applied to detect infectious pathogens in plant or animal tissues and clinical specimens (Rantakokko-Jalava & Jalava, 2001; Kuoppa et al., 2002; Wang et al., 2003; Watzinger et al., 2006; Ratcliff et al., 2007; Gil-Salas et al., 2007). More recently, this technique has also been used for the detection and quantification of noncultivable microbes (Li et al., 2006; Angelini et al., 2007), for the quantification of microorganisms in environmental samples such as in water (Gilbride et al., 2006) and soil (Sharma et al., 2007), and to characterize microbial communities (Kolb et al., 2003; Tsushima et al., 2006; Zhang & Fang, 2006; Cassler et al., 2007). From the works described in these past few years, it has become increasingly clear that this technique represents a powerful tool to analyse complex biological systems, where different organisms share their lives in such close contact that it is not possible to separate them and/or cultivate them separately. An example of such complexity is given by some arbuscular mycorrhizal fungi (AM) species, which are known to host bacterial populations inside their structures (Bonfante, 2003).

Arbuscular mycorrhizal fungi are obligate multinucleated biotrophic organisms, whose growth and hyphal development depend on their symbiotic association with plants, which provide them with mineral nutrients in exchange for carbon compounds (Smith & Read, 1997). Owing to their widespread presence in agricultural and natural soils, they represent an important microbial community of the rhizosphere. Despite the obvious significance of AM fungi in ecosystem functioning, so far little is known about their genetics and the organization of their genomes. The AM fungi are coenocytic, where many nuclei coexist in a common cytoplasm, and this leads to the question of whether they are heterokaryotic (Hijri & Sanders, 2005) or homokaryotic polyploid organisms (Pawlowska & Taylor, 2004).

Many Gigasporaceae represent a specialized niche for endocellular bacteria, which are consistently found throughout all the steps of the fungal life cycle. The most extensively studied AM fungus because of its endobacteria, is Gigaspora margarita isolate BEG 34, which was also the first fungus in which these prokaryotic cells were investigated and recognized as a homogeneous population (Bianciotto et al., 1996). On the basis of their ribosomal sequences, the endobacteria have been identified as a new bacterial taxon, Candidatus Glomeribacter gigasporarum (Bianciotto et al., 2003). The status of uncultivable microbe and its small genome (estimated as 1.4 Mb) (Jargeat et al., 2004) strongly suggests that Ca. Glomeribacter gigasporarum is an obligate endocellular bacterium, which is vertically transmitted from one fungal generation to the next (Bianciotto et al., 2004). In a recent study (Lumini et al., 2007), it has been reported how a protocol based on successive in vitro single-spore inocula of G. margarita caused a dilution of the microbial population, leading to bacteria-cured spores. The endobacteria were detected inside the fungus using both microscopy and PCR-based assays. The two methods resulted in a discrepancy in the number of spores detected as positive for the bacterial presence, suggesting a different level of sensitivity.

Since only a few protocols are available for microbes living in strict association with their hosts (Wang et al., 2003; Li et al., 2006; Angelini et al., 2007; Cassler et al., 2007), the aim of this investigation was to establish a quantitative method for the detection of Ca. Glomeribacter gigasporarum inside G. margarita by comparing nested PCR with qPCR. To do this, two genes from the endobacterium (23S rRNA gene and rpoB) and two from the fungus (18S rRNA gene and EF1-α) were chosen as amplification targets. The presumed single-copy status of the rpoB gene used in this analysis allowed us to define the minimum number of bacteria detectable in the fungal spores by qPCR as 10 bacterial genomes, and to indirectly confirm the single-copy status of the 23S rRNA gene. The qPCR method was then applied to other AM fungal structures (i.e. auxiliary cells, intraradical and extraradical mycelium), demonstrating its ability to detect and quantify both fungal and bacterial targets along the fungal life cycle.

Materials and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

DNA purification

Total DNA was extracted from the AM fungus G. margarita Becker and Hall (BEG 34; deposited at the European Bank of Glomeromycota). Spores with and without bacteria (wild type and cured spores) were produced and collected from clover pot cultures, as described in Lumini et al. (2007). The symbiotic fungal structures (i.e. intraradical and extraradical mycelium, and auxiliary cells) were obtained from mycorrhizal roots of Lotus japonicus inoculated using the sandwich method described in Novero et al. (2002) and sampled as described in Lanfranco et al. (2005).

Miniprep DNA extraction was performed for fungal spores and auxiliary cells, by crushing pools of 10 units in a volume of 50 µl of 1:1 H2O:10× RedTaq PCR buffer (100 mm Tris-HCl, pH 8.3, 500 mm KCl, 11 mm MgCl2 and 0.1% gelatine). After incubation at 95°C for 15 min, the crude extract was centrifuged at 10 000 g for 5 min, and the supernatant was used for 10-fold serial dilutions. Extreme care was taken to avoid external and cross-bacterial contamination, and all steps were carried out under a laminar flow hood.

For intraradical and extraradical mycelium the harvested fungal material was immediately frozen in liquid nitrogen (N) and homogenized using a Tissue Lyser mixer mill (Qiagen Inc., Valencia, CA, USA). DNA extraction was then carried out with a DNeasy Plant Mini Kit (Qiagen) according to the manufacturer's recommendations and with a final elution volume of 50 µl.

Primer design

In order to detect and quantify the nucleic acid of both the fungus and its bacterial endosymbiont, a ribosomal sequence and a translated specific gene were chosen for each organism as targets in the nested and qPCR assays. All the primers used in this study are listed in Table 1.

Table 1.  Polymerase chain reaction (PCR) primers used in this study (primers in bold were used in the nested and quantitative PCR, while the others were used in direct PCR)
 Target genePCR primer pair (5′–3′)Expected amplicon size
Bacterial target23S rRNA geneGlomGIGf: GGGTCCATTGCGGATTACTTC587 bp
GlomGIGr: GGGACCAGGACTTCCATCCCCC
23S rRNA geneGlomGIGf: GGGTCCATTGCGGATTACTTC 106 bp
GIGrA: GTTGTTGCCCTCTTGACACC
rpoBrpoBf-TCGCAGCTGTCGCAGTTCAT536 bp
rpoBr-CGCTGCATGTTCGAGCCCAT
rpoBRpoBRTf: CGCGGCAAAGTCACGGATAC 109 bp
RpoBRTr: ATCGGTGAGTGCGCCATCCTC
Fungal target18S rRNA geneNS31: TTGGAGGGCAAGTCTGGTGCC550 bp
AM1: GTTTCCCGTAAGGCGCCGAA
18S rRNA gene283f: GAATTTCTACCTTCTGGGGAACT106 bp
388r: TCAGACGTAAGCCTGCTTTG
EF1-αEfgigf: CGTTCCAATATCTGGTTGGCATGGTG289 bp
Efgig2r: GGTAAGACCAACTGGGGCGAATG
EF1-αEfgig2f: TGAACCTCCAACCAGACCAACTG103 bp
Efgigr: CGGTTTCAACACGACCTACAGGGAC

One set of primers consisted of the universal eukaryotic primer NS31 (Simon et al., 1992) and the primer AM1, which were designed to amplify AM fungal SSU sequences (Helgason et al., 1998). Primers 283f and 388r (Lanfranco et al., 2005), which amplify a more internal fragment of such a gene, were also used.

Three primers designed on the bacterial 23S ribosomal subunit of Ca. Glomeribacter gigasporarum (Acc. No. AJ561042) were used: GlomGIGf/GlomGIGr (Bianciotto et al., 2004) and the internal reverse primer GIGrA (Lumini et al., 2007).

Primers Efgigf and Efgig2r were designed on the basis of the gene for the translation elongation factor (EF1-α) that is available in the GenBank for the G. margarita isolate UY278.9 (Acc. No. AJ566400). These primers were used to amplify a 289 bp fragment on G. margarita BEG34 which was sequenced. Two nested primers Efgig2f and Efgigr were then designed.

The DNA-direct RNA polymerase β-subunit (rpoB) gene, which codes the RNA polymerase β-subunit, was used to design primers for the endobacterium detection. The rpoB sequences, which are available in the GenBank database, were aligned using the multiple sequence alignment programme clustalw (Thompson et al., 1994). The primers rpoBf and rpoBr were designed to detect a central fragment of 536 bp in the conserved region. On the basis of the sequence obtained, two specific internal primers, rpoBRTf and rpoBRTr, were derived for the nested and qPCR assays.

Sample preparation

Template DNA samples from both wild type and cured spores were quantified by spectrometry using the Thermo Scientific NanoDropTM ND-1000 instrument (NanoDrop Products, Wilmington, DE, USA), and then serially diluted in molecular grade water until the 10−6 dilution, to evaluate the sensitivity of the primer combinations in nested and real-time PCR assays.

Both the nested and qPCR assays were conducted in triplicate, on DNA extracted from three individual pools of 10 spores.

DNA samples from auxiliary cells, intraradical and extraradical mycelium were serially diluted until the 10−5 dilution and exclusively applied as template for Real-time qPCR assays.

Nested PCR assay

For direct PCR, the reactions were carried out both for the fungal and for the bacterial targets as described in Bianciotto et al. (2004), except for the annealing temperature, which was increased to 58°C.

For nested PCR, 1 µl of the PCR products obtained in the first round was added as a DNA template to 24 µl of PCR mix. The reaction mixture contained 10 mm Tris-HCl, 50 mm KCl, 1.5 mm MgCl2, 0.1% gelatine, 0.2 mm of each dNTP, 0.5 µm of each primer and 1 U of Taq polymerase. Amplifications were carried out in 0.2 ml PCR tubes using a Biometra TGradient thermocycler (Biometra biomedizinische Analytik GmbH, Goettingen, Germany). The programme consisted of 25 cycles of 45 s at 94°C, 45 s at 60°C, 45 s at 72°C and a final extension of 5 min at 72°C. The resulting PCR products were visualized in a 2.5% high resolution agarose gel using ethidium bromide for visualization with a Versadoc instrument (Biorad). The negative control of the direct PCR was included in the nested reaction to check for contamination or aspecific amplification.

Real-time PCR assay

Individual real-time qPCR reactions were assembled in a 20 µl reaction volume with 0.15 µm of each oligonucleotide primer, 10 µl of 2× iQTM SYBR Green Supermix (Bio-Rad, Hercules, CA, USA; containing 100 mm KCl, 40 mm Tris–HCl, pH 8.4, 0.4 mm dNTPs, 50 U µl−1 iTaq DNA polymerase, 6 mm MgCl2, 20 nm SYBR Green I and 20 nm fluorescein) plus 1 µl of appropriate DNA dilution. The PCR cycling programme consisted of 15 s at 95°C followed by 40 s at 60°C repeated for 40 cycles and included a heating step (3 min at 95°C) at the beginning of each run. Real time qPCR was carried out with ICycler apparatus (Bio-Rad). A melting curve (55–95°C) with a heating rate of 0.5°C per 10 s and a continuous fluorescence measurement was recorded at the end of each run to assess the amplification product specificity (Ririe et al., 1997). All reactions were performed with three technical replicates.

Template plasmids containing the target DNA sequences were used to generate a standard curve as an external standard. Plasmids were quantified by spectrometry with the ND-1000 instrument (Nanodrop) and copy numbers were estimated based upon the molecular weight of the template. From 106 to 101 copies of the serially diluted cloned target DNA were included in each run. The number of target DNA sequences present in each PCR mixture was calculated by comparing the crossing points of the samples with those of the standards using the ICyclersoftware (Bio-Rad, Hercules, CA, USA).

Nucleotide sequence accession number

The partial rpoB and EF1-α sequences have been deposited in the EMBL data library under accession nos. AM886448 and AM889024, respectively.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

The nucleic acid extracted from the spores and symbiotic structures of Gigaspora margarita, which was the template for the experiments described here, consists of a mixture of fungal and bacterial DNAs. Consequently, the specificity and sensitivity of the primer combinations were tested before the real-time quantification. Furthermore, since Ca. Glomeribacter gigasporarum is, to date considered an unculturable microbe, like its fungal host, plasmids with target DNA inserts were used for the construction of the standard curve for each target gene. After these first steps, serial dilutions of the mixed DNA were used to assess the technical limit of qPCR and nPCR in detecting the endobacterium inside its fungal host, and to quantify the minimum number of bacteria that can be revealed by qPCR.

Specificity and sensitivity of real-time assays

The specificity of the assays with the primer combinations was evaluated in real-time PCR on the basis of the melting curve obtained for each amplification product. The observation of a unique fluorescence fall at the fusion temperature that was specific for the PCR product showed that only a target-specific amplification occurred, and that no primer–dimer formation took place. Each primer set reacted well with its intended target (Ct values > 0) and no amplification was observed (Ct values = 0) for the negative controls (not shown).

The results demonstrated that the primer combinations were specific for their respective target sequences, and did not show any cross-reactivity with other sequences of either fungal or bacterial origin.

Figure 1 shows the fluorescence intensity plots throughout the amplification cycles, using a series of ten-fold dilutions of the total (fungal and bacterial) DNA from G. margarita spores, ranging from 10−1 to 10−5 for all the primer combinations. The linearity of the target quantity with the threshold cycles (Ct) testifies to the absence of an inhibition effect and the sensitivity of the amplification within such a DNA dilution range (Zhang & Fang, 2006). The amplification of the fungal 18S rRNA gene yielded a positive result until the 10−4 dilution of the DNA sample, while the last detectable dilution was 10−3 for the EF1-α gene and the bacterial genes rpoB and 23S.

image

Figure 1. Amplification profiles obtained with the primer combinations for the fungal 18S rRNA gene (a) and EF1-α (b), and the bacterial 23S rRNA gene (c) and rpoB (d). The templates were serial dilutions of total DNA extracted from Gigaspora margarita spores (1, 10−1; 2, 10−2; 3, 10−3; 4, 10−4; 5, 10−5).

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Generation of standard curves from plasmid DNA

Starting quantity standard curves (plasmid copy number) vs Ct were used to estimate the target quantities in the DNA samples (Fig. 2a,b for the fungal targets, c and d for the bacterial targets). The PCR fragments obtained for each primer combination used in this study were cloned inside plasmids and the inserts were verified by sequencing. Purified plasmid preparations were quantified using a spectrophotometer and the copy numbers were calculated. Serial plasmid dilutions were applied to each run to define the sensitivity of the method. Since the precision of microbial quantification using qPCR relies on the assumption that the unknown sample and the standard solutions share the same PCR efficiency, we verified whether the PCR efficiency in the analysis of both the standard solutions and samples were the same. As few as 10 copies per reaction were detected for each target sequence, and quantification of the initial copy numbers was linear over a range of 106 to 10 copies of plasmid standard DNA.

image

Figure 2. Serial dilutions of plasmids with the target DNA insert were used in individual quantitative polymerase chain reaction (PCR) assays to generate standard curves for the 23S rRNA gene (a), rpoB (b), 18S rRNA gene (c) and EF1-α (d). The R2 values and slopes are shown for each reaction.

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Detection limit and quantification studies

On the basis of the previously described system setup, qPCR was used to detect and quantify fungal and bacterial target sequences. The reactions were conducted on DNA extracted from three individual pools of 10 spores. These three dilution series (from 10−1 to 10−5), which originated from independent extractions, gave similar results, suggesting that the yield of the DNA extractions was similar (data not shown). Three dilution series (from undiluted to 10−5) of DNA extracted from cured spores were also included in the analysis. No signal was detected when the bacterial primers were used, thus confirming the absence of the endobacteria. The Cts obtained when the fungal targets were tested on cured spores were comparable to that from the wild-type spore condition (Table 3).

Table 3.  Sensitivity of quantitative and nested polymerase chain reaction (qPCR and nPCR, respectively) for the detection of both fungal and bacterial targets
DNA serial dilutionBacterial targetsFungal targets
23S rRNA generpoB18S rRNA geneEF1-α
qPCRnPCRqPCRnPCRqPCRnPCRqPCRnPCR
  1. The threshold cycles (Cts) for all the dilutions tested are listed for qPCR; when Ct = 0 no amplification signal was detected. The presence (+) or the absence (−) of a band on an analytical agarose gel is reported for nested PCR. The amplification results of the 10−1 dilution are reported for the cured condition.

10−125.84+28.67+23.62+28.22+
10−229.1+31.91+26.79+31.56+
10−332.66+34.62+29.75+34.1+
10−40032.51+0
10−50000
10−60000
Water0000
Cured 10−10022.91+28.89+

The bacterial detection was performed targeting the 23S rRNA gene and the rpoB genes, which have both recently been predicted to be present in single copy in the Ca. Glomeribacter genome through a sequencing approach which is in progress (S. Ghignone, pers. comm.).

Two fungal genes, 18S ribosomal DNA (18S rRNA gene) and elongation factor alpha (EF1-α) were amplified as positive internal controls. The amplification of the 18S rRNA gene yielded a positive result until the 10−4 dilution of the DNA sample, while the last detected dilution was 10−3 for the EF1-α gene. Ribosomal genes are often present in repeated copies in eukaryotes (Perry, 1976; Alkan et al., 2004), and it is still unclear whether G. margarita contains multiple ribosomal sequences in its genome. The EF1-α gene has instead already been used as a single-copy gene in AM fungi phylogenetic studies (Helgason et al., 2003).

As shown in Table 2, primers targeting single-copy genes (bacterial rpoB and fungal EF1-α) gave a positive result (Ct > 0) until the same 10−3 DNA dilution, as well as 23S rRNA gene which was therefore predicted to be a single copy gene. On the basis of the resulting standard curve amplification, it was estimated that this 10−3 dilution contains at least 10 target sequence copies. Therefore, as can be inferred for the single-copy genes, it is possible to conclude that the technical limit of qPCR is of 10 genomes for both bacterial and fungal detection in each PCR mixture. This corresponds to the detection of 10 bacterial cells, and, owing to the multinucleate status of G. margarita, to 10 fungal nuclei. For the 18S ribosomal sequence, the last signal in a 10-fold more diluted DNA solution than for the EF1-α gene, that is, in the 10−4 dilution, was always detected.

Table 2.  Quantification of the minimum number of target sequences detected with quantitative polymerase chain reaction (PCR) on the basis of the comparison between the threshold cycles (Cts) obtained for the DNA samples and that of the recombinant plasmids used to construct each gene-specific standard curve
 Target geneLast dilution detectedCtEstimated copy numberPCR efficiency (%)
BacterialrpoB10−334.6210107.3
23S rRNA gene10−332.661099.2
FungalEF1-α10−334.11099.3
18S rRNA gene10−432.5110102.4

As can be noted in Table 2, the last detected dilution for all the considered primer combinations corresponds to 10 sequence copies per PCR mixture, suggesting that the method is equally sensitive for the detection of both fungal and bacterial targets.

Comparison of nested and qPCR

Nested PCR assays (nPCR) were performed on the same DNA serial dilutions that were used for the qPCR experiments.

As has previously been demonstrated (Lumini et al., 2007), nPCR increased the sensitivity of the conventional PCR to detect Ca. Glomeribacter gigasporarum inside the fungal spores, with an at least 10-fold improvement. The nPCR assay, which was used in this study to detect the endobacterium, showed both high sensitivity and high specificity.

All the samples for which nPCR gave positive results were confirmed by qPCR for both fungal and bacterial detection. Even for the lowest target concentration (corresponding to dilutions 10−3/10−4), nPCR amplification products were clearly visible on agarose gel stained with ethidium bromide (Fig. 3). For the 23S rRNA gene, rpoB and EF1-α genes, an amplification signal was obtained until the 10−3 dilution of sporal DNA with both nested and qPCR, while the 18S rRNA gene sequence was also detected in the 10−4 dilution with both techniques. The samples that were found to be negative with nPCR, were also negative with qPCR.

image

Figure 3. Agarose gel electrophoresis patterns of the nested polymerase chain reaction (nPCR) amplification targeting (from left to right) 18S rRNA gene, EF1-α, 23S rRNA gene and rpoB genes. Samples: 0, water; 1–5, DNA dilutions 10−1, 10−2, 10−3, 10−4, 10−5, respectively; L, ladder.

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Similar sensitivity and specificity were found for qPCR and nPCR, as can be seen in Table 3. This agreement of results indicates that the sensitivity of the nPCR protocol, followed by agarose gel resolution, was comparable to that of qPCR in detecting small amounts of target DNA. Thus, it can be concluded that the detection limit of qPCR is of the order of 10 bacterial genomes for each PCR mixture and, consequently, it is the same as that found with for nPCR.

Detection and quantification of bacteria from symbiotic mycelia and auxiliary cells

As an additional step, the qPCR method was applied to other AM fungal structures, namely, auxiliary cells (AUX) and extraradical and intraradical mycelium (EM and IM, respectively), in order to assess whether the technique was suitable to detect and quantify both fungal and bacterial targets throughout the fungal life cycle.

In accordance with the data obtained from the assays performed on sporal DNA, all the primers succeeded in detecting as few as 10 target copies in all conditions. All the primer pairs (fungal and bacterial) showed the same behaviour, which had previously been observed for the sporal condition (data not shown).

The qPCR methodology, which enables the estimation of the starting target quantities based on the amplification Cts, allows organisms in samples (or nuclei for multinucleate organisms) to be quantified when single-copy genes are considered. This allowed determination of a bacterial–fungal ratio (number of bacteria vs number of fungal nuclei detected) for each sample, by taking the fungal EF1-α and bacterial rpoB quantification into consideration. This ratio can be compared for different samples, so any problem caused by inhomogeneity of the starting material can be overcome.

Following this analysis, this ratio was found to be consistently higher in the EM samples than in the IM and AUX samples (Table 4). This interesting difference may suggest that the bacteria/fungal nuclei ratio is higher in the EM sample than in the IM, and AUX samples, suggesting that extraradical mycelium may be a preferential site for bacterial division. The ratio detected in the previous experiment on spores was also consistent with the data obtained from the IM and AUX samples (not shown).

Table 4.  Relative quantification of bacterial/fungal single copy targets obtained by quantitative and nested polymerase chain reaction
 rpoB copy numberEF1-α copy numberrpoB/EF1-α
  1. The gene copy number was calculated by interpolation of the samples’ threshold cycles (Cts) in the standard curve constructed on the plasmid dilutions. The copy number was estimated on the same template dilution for both the bacterial and the fungal target. IM, intraradical mycelium; EM, extraradical mycelium; AUX, auxiliary cells.

IM43261.65
EM430656.62
AUX35191.84

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

The assessment of the detection limit is a technical problem of great importance, especially in the diagnostics of infectious agents. Papers have already been published which calculate the detection limit of free-living microbes (Wellinghausen et al., 2001; Nadkarni et al., 2002; Rao et al., 2006): such experiments are usually based on the ‘weight’ of a single bacterial cell with a known genome. In these cases, it is possible to use a quantitative real-time based method for microbe detection, conducting a quantification that is based on the minimum number of detected genome copies. Because of their high sensitivity and discriminatory power, PCR-based techniques represent one of the most frequently used methodologies to study complex biological systems.

Here, we demonstrated how a combined approach based on nPCR and qPCR was successful in detecting and quantifying the Ca. Glomeribacter gigasporarum population that lives inside the AM fungus G. margarita.

Since Ca. Glomeribacter gigasporarum is to date considered an unculturable microbe, like its fungal host, a plasmid carrying the target cloned sequence was used to construct the standard curve for quantification studies. In qPCR, we demonstrated that the last detectable dilution corresponded, in each case, to 10 copies of the target sequences in the plasmid, suggesting that the sensitivity of the method was the same for the detection of both fungal and bacterial targets.

Comparisons of nPCR and qPCR have often revealed a different degree of sensitivity, depending on the biological system to which the two techniques were applied (Fang et al., 2002; Anderson et al., 2003; Amos et al., 2007; Angelini et al., 2007). In addition to the level of sensitivity, some practical aspects should be considered: nested PCR assays require up to 5 h 30 min for the first- and second-round PCR amplifications, agarose gel electrophoresis, ethidium bromide staining, and resulting analysis. Real-time PCR can instead be performed in < 1 h in a single capillary tube without opening the reaction tube, thereby significantly reducing the PCR running time and the probability of cross-contamination. Furthermore, the specificity of the qPCR product can be verified simply by analysing the melting temperature after the PCR run. Thus, real-time qPCR provides a rapid and reliable tool for qualitative and quantitative analyses. Here, the results obtained both for the fungal and bacterial detection showed that the sensitivity of the SYBR Green-based qPCR protocol was comparable to that of a nPCR protocol which includes the use of ethidium bromide-stained agarose gel for product visualization in our laboratory conditions (Lumini et al., 2007).

The selected genes represent a second original aspect of this study. The rpoB gene was used for the first time, in addition to ribosomal sequence 23S, for the detection of the endobacterium. While the ribosomal operon may be present in multiple copies in prokaryotes, the rpoB gene is considered a single-copy gene. The DNA-direct RNA polymerase β-subunit (rpoB) gene, which encodes the RNA polymerase β-subunit, is a highly conserved housekeeping gene, and is present in all bacteria because of its essential role in cellular metabolism (Qi et al., 2001). It has been used as a signature for bacterial identification and, because of its discriminatory power, as a locus for phylogenetic analysis (Mollet et al., 1997). Both the selected bacterial genes (23S rRNA gene and rpoB) are predicted to be present in Ca. Glomeribacter gigasporarum as single-copy genes, on the basis of the currently ongoing sequencing project (S. Ghignone, pers. comm.). In both cases, a positive amplification signal (Ct > 0) was obtained until the 10−3 sporal DNA dilution, which corresponds to the detection of 10 target copies. This finding suggests that they are present in the bacterial genome in a 1 : 1 ratio, strengthening the belief that they are present in single copy.

The detection and amplification of bacterial sequences in diluted templates from symbiotic mycelia and auxiliary cells offer novel information on the bacterial life cycle: the comparable fungal/bacterial ratios detected in spores, intraradical mycelium and auxiliary cells suggest that the bacteria keep their dealings with the fungal component more or less constant, regardless of whether they are contained inside spores, auxiliary cells or mycorrhizal roots. The fungal/bacterial ratio detected in the extraradical mycelium instead suggests that these structures may be the preferential site for bacterial division, according to unpublished results (I. A. Anca et al., unpublished).

Even though the primary aim of this investigation was bacterial detection and its quantification inside the fungal host, the simultaneous amplification of two fungal targets (18S rRNA gene and EF1-α) offered some additional information on the fungal side. A number of studies have used 18S rRNA to study and detect AM fungi with molecular biology techniques (Simon et al., 1993; Trouvelot et al., 1999; Kuhn et al., 2001; Alkan et al., 2004; Alkan et al., 2006). Since it has not yet been stated how many copies of ribosomal sequences are present in G. margarita, and given that ribosomal genes are often present in repeated copies in eukaryotes (Perry, 1976; Alkan et al., 2004), a protein coding gene that is usually present in single copy was also chosen for our analysis. The EF1-α gene encodes the translation elongation factor that controls the rate and fidelity of protein synthesis (Baldauf et al., 1996) and it has already been used as a single-copy gene to study AM fungal phylogeny (Helgason et al., 2003).

We always detected the last amplification signal from the 18S rRNA gene in a 10-fold more diluted DNA solution than for the EF1-α gene; this could mean that the two genes are represented in the G. margarita genome with a ratio of c. 10 : 1. This fact suggests that multiple copies of ribosomal sequences could be present in AM fungi, confirming the results obtained by other authors with the fluorescence in situ hybridization (FISH) technique (Trouvelot et al., 1999; Kuhn et al., 2001). Interestingly, the detection limit of both the fungal genes was unchanged in the cured spores compared to the wild type, confirming that the repeated monosporal fungal generations, required to originate the cured line, did not have a dramatic impact on the fungal genome organization (Lumini et al., 2007).

In conclusion, our results offer a first attempt to reply to a clear need for the establishment of methods that allow quantification of the bacteria interacting with eukaryotic hosts in the fields of medical and environmental microbiology. Leveau & Preston (2008) recently reviewed many complex biological systems where bacteria develop specific strategies to obtain nutrients from fungi, with important ecological consequences in many environments. Since one of the priorities in this context is to demonstrate the impact of the bacteria on the structure and activity of fungal communities, the development of methodologies to quantify the bacterial presence is a priority. The method we have developed opens new perspectives to face such problems, since the experimental set-up described can be used to follow not only bacteria, but also the eukaryotic partner throughout all the life cycle stages. Owing to the high sensitivity of the method (as few as 10 fungal nuclei can be potentially detected), this study represents a step forward concerning the use of PCR based-techniques for AM fungi traceability, as it allows the detection of short hyphal fragments in environmental samples.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

This work was supported by IPP-CNR (AG-P02-006 Biodiversity Project-Torino), Compagnia di San Paolo, SOILSINK Project (FISR), ENDURE NoE EU project and TRACEAM EU project (MEST-CT-2005-021016). E.L. was funded by SOILSINK.

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  3. Introduction
  4. Materials and Methods
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  6. Discussion
  7. Acknowledgements
  8. References
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