This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowReprints and Permissions
Right arrow Copyright Information
Right arrow Books from ASM Press
Right arrow MicrobeWorld
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Schwarzenbach, K.
Right arrow Articles by Enkerli, J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Schwarzenbach, K.
Right arrow Articles by Enkerli, J.
Agricola
Right arrow Articles by Schwarzenbach, K.
Right arrow Articles by Enkerli, J.

 Previous Article  |  Next Article 

Applied and Environmental Microbiology, October 2007, p. 6519-6525, Vol. 73, No. 20
0099-2240/07/$08.00+0     doi:10.1128/AEM.01405-07
Copyright © 2007, American Society for Microbiology. All Rights Reserved.

Cultivation-Independent Analysis of Fungal Genotypes in Soil by Using Simple Sequence Repeat Markers{triangledown}

Kaspar Schwarzenbach, Franco Widmer, and Jürg Enkerli*

Molecular Ecology, Agroscope Reckenholz-Tänikon Research Station ART, Reckenholzstrasse 191, 8046 Zürich, Switzerland

Received 25 June 2007/ Accepted 12 August 2007


arrow
ABSTRACT
 
Cultivation-independent analyses of fungi are used for community profiling as well as identification of specific strains in environmental samples. The objective of the present study was to adapt genotyping based on simple sequence repeat (SSR) marker detection for use in cultivation-independent monitoring of fungal species or strains in bulk soil DNA. As a model system, a fungal biocontrol agent (BCA) based on Beauveria brongniartii, for which six SSR markers have been developed, was used. Species specificity of SSR detection was verified with 15 fungal species. Real-time PCR was used to adjust for different detection sensitivities of the six SSR markers as well as for different template quantities. The limit for reliable detection per PCR assay was below 2 pg target DNA, corresponding to an estimated 45 genome copies of B. brongniartii. The cultivation-independent approach was compared to cultivation-dependent SSR analysis with soil samples from a B. brongniartii BCA-treated field plot. Results of the cultivation-independent method were consistent with cultivation-dependent genotyping and allowed for unambiguous identification and differentiation of the applied as well as indigenous strains in the samples. Due to the larger quantities of soil used for cultivation-dependent analysis, its sensitivity was higher, but cultivation-independent SSR genotyping was much faster. Therefore, cultivation-independent monitoring of B. brongniartii based on multiple SSR markers represents a rapid and strain-specific approach. This strategy may also be applicable to other fungal species or strains for which SSR markers have been developed.


arrow
INTRODUCTION
 
Characterization and monitoring of fungi in the environment are important aspects for many research questions in fungal biology and ecology. These include, for example, characterization of fungal population structures (5, 44), investigations of fungal functions in ecosystems (34) or natural occurrence of specified fungal groups, e.g., entomopathogenic fungi (33), and studies of survival, spread, and persistence of fungal strains released to the environment (4, 16). Traditionally, identification and characterization of fungi has relied on cultivation, followed by morphological (26), biochemical (35, 40), or molecular (15) analyses. However, the cultivation step required makes these approaches both laborious and time-consuming.

Cultivation-independent molecular genetic detection of fungal populations directly in DNA extracted from complex environmental samples could reduce the time and cost for monitoring and analysis (8). Such analyses have successfully been applied to fungal community profiling and are highly valuable for analyzing population structures at various phylogenetic levels (1). Typically, specific PCR primers target conserved regions in phylogenetic markers, like the small as well as the large subunit of rRNA genes or their internal transcribed spacer regions. However, limited resolution often does not allow for identification of particular strains based on these markers (1). For identification of specific fungal groups in complex environmental samples, specific primers have been designed within variable regions of marker genes, such as the internal transcribed spacer region (2, 17) or sequence-characterized amplified regions (10, 13, 14). Because specificity of a single marker may be limited to particular ecosystems or a range of tested strains, the use of multiple markers would improve reliability and resolution of such analyses (23, 46).

Multilocus simple sequence repeat (SSR) genotyping is a commonly used technique for characterization of cultivated fungi based on PCR amplification of multiple markers (loci). The polymorphic character of SSRs produces highly discriminating fingerprints that often allow characterization of fungi at a strain level (3, 12, 16). Several fungal SSR markers have been reported to be species specific (3, 39, 46), and therefore multilocus SSR genotyping may be a promising option for cultivation-independent detection of fungal strains in soil samples (8). However, it is important to notice that detection sensitivities of individual SSR markers can be different (7, 20). Thus, in cultivation-independent analyses of environmental templates, SSR-specific detection sensitivities would have to be adjusted for reliable multilocus genotyping.

The filamentous ascomycete Beauveria brongniartii is a naturally occurring soil fungus and pathogen of the European cockchafer (Melolontha melolontha), a pest in permanent grasslands and orchards (28). Since 1991, B. brongniartii has been available as a commercial biocontrol agent (BCA) to control soil-dwelling larvae of M. melolontha (29). A cultivation-dependent monitoring approach based on six polymorphic SSR markers has been developed (15) and has successfully been used to characterize natural soil populations of B. brongniartii and to monitor applied BCA strains (16).

The objective of the present study was to develop a cultivation-independent approach for SSR genotyping of B. brongniartii strains in soil. For this purpose, the six B. brongniartii SSR primer pairs were tested for species specificity and performance in bulk soil DNA extracts. Sensitivities for detecting the different SSR loci were determined, and differences were adjusted by adapted PCR conditions. A grassland plot treated with a commercially available B. brongniartii BCA strain was used as a model system to compare efficiencies and sensitivities of the established cultivation-dependent and the new cultivation-independent SSR genotyping approaches.


arrow
MATERIALS AND METHODS
 
Fungal reference strains.
Fifteen reference strains, including typical soil fungal species, close relatives of B. brongniartii, and other entomopathogenic fungi, were obtained from several culture collections (Table 1). Reference strains were grown at 22°C for 3 weeks on Difco modified Sabouraud agar supplemented with Difco yeast extract (Becton Dickinson, Sparks, MD) (37). Egg yolk (17%) was added to the medium for growing the Entomophthorales strains (37).


View this table:
[in this window]
[in a new window]

  		TABLE 1. Detection specificity of six B. brongniartii SSR markers tested on a collection of 15 fungal reference strains, including ubiquitous soil fungal species, close relatives of B. brongniartii, and other entomopathogenic fungi

Field application of the B. brongniartii BCA strain and soil sampling.
Field experiments were carried out in an M. melolontha-infested hay meadow with a humus-rich eutric cambisol. Two adjacent plots of 400 m2 (20 by 20 m) each were either treated with the commercially available B. brongniartii BCA product Beauveria-Schweizer (E. Schweizer Seeds Ltd., Thun, Switzerland) or left as an untreated control. The BCA product consisting of barley kernels overgrown with B. brongniartii strain DSMZ 15205 (BCA strain) was applied once in spring 2002 in quantities of 40 to 50 kg ha–1 (30). In September 2004, five soil samples from the treated plot (T1 to T5) and from the untreated control (C1 to C5) were collected. At each of the evenly distributed sampling points, two adjacent soil cores were taken using a stainless-steel corer with an internal diameter of 5.5 cm. The 5- to 15-cm-depth fractions of adjacent cores were pooled (30) and stored at 4°C until use (see below).

B. brongniartii density and field isolates.
Within 2 weeks after sampling, B. brongniartii density in each soil sample was determined. Twenty grams of soil was mixed with 100 ml of 4 mM tetra-sodiumpyrophosphate (Na4P2O7·10H2O) and suspended at room temperature for 2 h at 110 rpm (29). After sedimentation for 15 s, 100-µl aliquots of the supernatant were plated in triplicate on solid selective medium (SM) (43). After incubation for 14 days at 22°C, densities of B. brongniartii were determined as numbers of CFU per gram soil (dry weight). B. brongniartii isolates were obtained from single colonies randomly picked from SM plates, transferred to solid complete medium (41), and maintained at 22°C.

Extraction of genomic DNA.
Mycelia for DNA extraction were produced by inoculation of 80 ml liquid complete medium with conidia collected from plates and growth for 2 to 6 days at 20°C at 120 rpm. Mycelia were harvested by filtration as described by Enkerli et al. (15). Genomic DNA was extracted from lyophilized mycelium by using a DNeasy plant mini kit (QIAGEN, Hilden, Germany) and quantified by gel electrophoresis using a GelDoc XRS (Bio-Rad Laboratories, Hercules, CA) gel imaging system with Quantity One analysis software (Bio-Rad Laboratories) and a high-mass DNA ladder (Promega, Madison, WI) as the standard. The suitability of DNA for PCR was tested by amplifying the 18S rRNA gene with universal primers SSU-uni-b-for (5'-TGCCAGCMGCCGCGGTA-3') (modified from reference 19) and SSU-uni-b-rev (5'-GACGGGCGGTGTGTRCAA-3') (6). PCR was performed on an iCycler (Bio-Rad Laboratories) in volumes of 25 µl containing 20 ng DNA, 1 U HotStart Taq polymerase (QIAGEN), 1x PCR buffer (QIAGEN), 2.5 mM MgCl2, 0.2 µM of each primer, 0.4 mM deoxynucleoside triphosphate, and 0.6 mg ml–1 bovine serum albumin (BSA). Cycling conditions consisted of a 15-min initial denaturation at 95°C and 30 PCR cycles of 25 s at 92°C, 40 s at 53°C, and 3 min at 72°C, followed by a final extension for 10 min at 72°C. The quality of amplification products was confirmed by gel electrophoresis in 1.5% agarose gels and ethidium bromide staining.

Analysis of SSR markers in fungal genomic DNA.
SSR marker detection for the six SSR loci Bb1F4, Bb2A3, Bb2F8, Bb4H9, Bb5F4, and Bb8D6 from B. brongniartii was performed according to the method of Enkerli et al. (15). Reaction volumes of 25 µl contained 20 ng genomic template DNA, 12.5 µl iQ SYBR green supermix (Bio-Rad Laboratories), 0.2 µM of fluorescently labeled forward primer, 0.2 µM of unlabeled reverse primer, and 0.6 mg ml–1 BSA. Cycling conditions consisted of a 3-min initial denaturation at 95°C and 36 PCR cycles of 40 s at 92°C, 40 s at 58°C, and 30 s at 72°C, followed by a final extension of 10 min at 72°C.

Detection sensitivities for the six SSR markers were compared based on cycle threshold (CT) values of each primer pair determined from 2 pg genomic DNA of the BCA strain running real-time PCR with the same conditions as described above, except that 45 PCR cycles were applied. Real-time PCR data were analyzed using an iCycler iQ real-time PCR detection system and software v3.1 (Bio-Rad Laboratories). For comparison of detection sensitivities of the six loci, differences in CT values were expressed as relative CT (CT-rel) values, calculated as quotients between CT values of the most efficiently amplified SSR locus, Bb4H9 (CT-4H9), and CT values of each of the other five SSR loci.

PCR products were analyzed for SSR sizes and the presence of SSR characteristic stutter peak patterns on an ABI Prism 3100 genetic analyzer with 36-cm capillaries and POP-4 polymer (Applied Biosystems, Foster City, CA). For that purpose, 20 µl PCR product was purified (Montage PCR cleanup kit; Millipore, Bedford, MA), resuspended in 50 µl TE buffer (10 mM Tris-HCl, 1 mM EDTA, pH 8), and further diluted 1 to 10. Two microliters of the diluted product was used for analysis. GeneScan ROX400 (Applied Biosystems) was used as an internal size standard, and signals were analyzed using GeneScan v3.7 and Genotyper v3.7 NT analysis software (Applied Biosystems).

SSR analysis in bulk soil DNA.
Nucleic acids were extracted within 48 h after collection of soil samples. Six hundred milligrams fresh soil was extracted three consecutive times by using a bead-beating procedure, and bulk soil DNA of each sample was pooled and suspended in TE buffer at 1 ml g–1 (dry weight equivalent) of extracted soil (21). Twenty-five microliters of each extract was purified using NucleoSpin Extract-II DNA purification columns (Macherey & Nagel, Easton, PA) and quantified fluorometrically with PicoGreen (Molecular Probes, Eugene, OR) according to the method of Hartmann et al. (21).

The potential to amplify the six B. brongniartii SSR markers from bulk soil DNA was assessed with 50 ng B. brongniartii-free bulk soil DNA from sample C1 spiked with 2 pg of genomic DNA of the BCA strain (spiked-soil DNA). Prior to PCR, soil DNA was incubated with 30 µg BSA in a volume of 12 µl for 45 min at 37°C in order to scavenge PCR inhibitory substances present in the soil DNA extract (32). CT and CT-rel of spiked-soil DNA were determined for each SSR locus as described above for genomic DNA of the BCA strain.

The potential to detect multiple genotypes of B. brongniartii in bulk soil DNA was tested using 50 ng of B. brongniartii-free bulk soil DNA from sample C1 spiked with various combinations of 20, 2, or 0.2 pg genomic DNA from three different genotypes (I, II, and III) of B. brongniartii (Table 2).


View this table:
[in this window]
[in a new window]

  		TABLE 2. SSR fingerprints of the three B. brongniartii strains

Variable template quantities in soil samples as well as differences in locus-specific detection sensitivities were accounted for by the use of adapted amplification cycle (Ca) numbers. The Ca values were determined in a three-step process for each of the 10 field soil samples and each locus. First, CT-4H9 was determined experimentally in duplicate from each of the 10 field soil samples. Second, CT values of loci Bb1F4, Bb2A3, Bb2F8, Bb5F4, and Bb8D6 were calculated as products of averaged CT-4H9 and corresponding CT-rel values derived from spiked-soil DNA. Third, obtained CT values were grouped in classes of adapted cycle numbers according to the following rules: Ca-28 for CT of <30, Ca-32 for 30 ≤ CT < 34; Ca-36 for 34 ≤ CT < 38; and Ca-40 for CT of ≥38. Therefore, PCR was run at 28, 32, 36, or 40 cycles according to Ca and amplification products were analyzed for SSR sizes and characteristics as described for genomic DNA of the BCA strain.


arrow
RESULTS
 
Specificity of B. brongniartii SSR marker detection.
SSR analysis of the 15 reference strains revealed specific PCR amplifications from B. brongniartii with typical SSRs for all six loci Bb1F4, Bb2A3, Bb2F8, Bb4H9, Bb5F4, and Bb8D6 (Fig. 1a for locus Bb2F8 and Table 1). From Beauveria bassiana, one typical SSR product (163 bp) was obtained for locus Bb8D6 (Table 1). For the other loci tested, PCR products with lengths of 191 bp (locus Bb1F4), 203 bp (locus Bb4H9), and 133 bp (locus Bb5F4) were obtained from B. bassiana, and for locus Bb1F4 a product of 191 bp was obtained from Trichoderma harzianum; however, analyses revealed no SSR characteristic stutter patterns for these PCR products and they were therefore considered unspecific (data not shown). DNA of all reference strains was suitable for PCR as revealed by positive-control PCR using universal primers for the small-subunit rRNA gene (Fig. 1b).


Figure 1
View larger version (30K):
[in this window]
[in a new window]

  		FIG. 1. Gel electrophoretic analyses of PCR products derived from the 15 fungal reference strains specified in Table 1. (a) The band at about 200 bp represents the PCR product for SSR locus Bb2F8 separated in 1.5% agarose. (b) The bands between 1,000 and 1,500 bp represent PCR products obtained with the universal primer pair targeting the small-subunit rRNA gene separated in 1.5% agarose. Marker, 1-kb DNA ladder (Promega).

Sensitivity of cultivation-independent SSR detection.
The PCR amplification efficiency for each of the six SSR loci was determined for 2 pg genomic DNA of the BCA strain and resulted in CT values ranging from 28.83 ± 1.86 (locus Bb4H9) to 34.57 ± 0.65 (locus Bb2A3) (Table 3). PCR detection in 50 ng bulk soil DNA from Beauveria-free sample C1 that was spiked with 2 pg genomic DNA of the BCA strain (spiked-soil DNA) resulted in values not significantly different (P < 0.05, two-sided Student's t test) from the results with pure genomic DNA (Table 3). The CT values for these analyses ranged from 28.53 ± 0.68 (locus Bb8D6) to 34.35 ± 1.09 (locus Bb2A3). CT-rel values (with reference to locus Bb4H9) ranged from 1.02 (locus Bb8D6) to 1.20 (locus Bb2A3) for genomic DNA from the BCA strain and from 0.99 (locus Bb8D6) to 1.20 (locus Bb2A3) for spiked-soil DNA (Table 3).


View this table:
[in this window]
[in a new window]

  		TABLE 3. CT values for PCR amplification of six B. brongniartii SSR loci and corresponding CT-rel values

Simultaneous detection of multiple genotypes in bulk soil DNA.
The sensitivity for detecting multiple genotypes of B. brongniartii in bulk soil DNA was tested again using 50 ng Beauveria-free bulk soil DNA extract of sample C1 spiked with different quantities of genomic DNA from three different genotypes of B. brongniartii (Tables 2 and 4). All three genotypes had a common allele at locus Bb8D6, and genotypes I and II were identical at locus Bb2A3 (Table 2).


View this table:
[in this window]
[in a new window]

  		TABLE 4. Detection of genotype-specific alleles of six SSR loci in 50 ng B. brongniartii-free bulk soil DNA spiked with mixtures of different quantities of three different genotypes of B. brongniartii

Marker detection sensitivities for this experiment were adjusted according to the total quantities of spiked genomic DNA and according to the relative efficiencies of the six loci according to CT-rel (Table 3). For mixtures containing a minimum of 6 pg spiked genomic template DNA (Table 4, mixtures a to c), cycle numbers for the more efficiently amplifying loci Bb4H9, Bb5F4, and Bb8D6 were set to 28 cycles and for the less efficiently amplifying loci Bb1F4, Bb2A3, and Bb2F8 to 32 cycles. For mixtures with less than 6 pg spiked genomic DNA (Table 4, mixtures d and e), the more efficiently amplifying loci were processed at 36 PCR cycles while the less efficiently amplifying loci were processed at 40 PCR cycles.

The unambiguous assignment of fingerprints to individual genotypes was possible for spiked genomic DNA quantities of 2 pg or 20 pg (Table 4, mixtures a to d). Analysis of samples with 0.2 pg spiked genomic DNA of a specific genotype yielded incomplete corresponding fingerprints, and thus no genotype could be assigned. In mixture b, containing 0.2 pg DNA of genotype I and 20 pg DNA each of genotypes II and III, genotype I-specific alleles at loci Bb1F4 and Bb5F4 were detected, but those of loci Bb2F8 and Bb4H9 were not detected. In mixture d, containing 0.2 pg spiked genomic DNA of genotypes II and III, genotype II alleles that are shared with genotype I (locus Bb2A3) or common to all three genotypes (locus Bb8D6) were detected. In mixture e, containing 0.6 pg DNA, i.e., 0.2 pg of each of the three genotypes, the shared allele at locus Bb8D6 and the genotype I-specific allele at locus Bb4H9 were detected (Table 4).

Cultivation-dependent analyses of B. brongniartii field populations.
Plating on SM revealed the presence of B. brongniartii in all five soil samples (T1 to T5) from the field plot treated with the BCA strain (Table 5). The mean B. brongniartii density was 98,484 CFU g–1 (dry weight), with a minimum of 9,405 CFU g–1 (dry weight) (sample T3) and a maximum of 229,266 CFU g–1 (dry weight) (sample T2). From the control plot, two samples were free of B. brongniartii, while two samples contained B. brongniartii at low densities (261 and 816 CFU g–1 [dry weight]) and one sample contained B. brongniartii at the highest density observed, i.e., 724,441 CFU g–1 (dry weight). Genotypes of 24 isolates from the plating experiment were characterized by analysis of the six B. brongniartii SSR loci (Table 5). Three different genotypes were identified (Table 2). Genotype I of the applied BCA strain as well as indigenous genotype II was detected for 14 B. brongniartii isolates randomly selected from the treated plot (Table 5). A different indigenous genotype (genotype III) was found exclusively in 10 isolates from the control plot (Table 5). Genotypes I and II displayed the same allele at locus Bb2A3, while all three genotypes had a common allele at locus Bb8D6 (Table 2).


View this table:
[in this window]
[in a new window]

  		TABLE 5. Monitoring of B. brongniartii in a BCA-treated plot (samples T1 to T5) and in a control plot (samples C1 to C5)

Cultivation-independent analysis of B. brongniartii field populations.
DNA extraction from the 10 field soil samples yielded 261 to 299 µg DNA g–1 (dry weight) for the treated plot and 287 to 350 µg DNA g–1 (dry weight) for the control plot. Mean quantities of 276 µg DNA g–1 (dry weight) for the treated plot and 300 µg DNA g–1 (dry weight) for the untreated plot were not significantly different (P < 0.05, two-sided Student's t test).

Relative differences of SSR detection sensitivities (CT-rel) derived from bulk soil DNA spiked with genomic DNA (spiked-soil DNA) (Table 3) were confirmed with field soil samples. Correlation coefficients between experimentally determined CT values and CT values calculated as products of CT-4H9 and corresponding CT-rel from spiked-soil DNA were r = 0.99 for soil sample T2, with high B. brongniartii plate counts, and r = 0.93 for soil sample T3, with 24-times-lower plate counts.

Values for CT-4H9 varied between 26.4 and 35.2 among 8 of the 10 soil samples, with a maximum difference of 1.1 cycles for duplicate analyses. Based on these results, Ca values were set to 28, 32, 36, or 40 cycles (Tables 3 and 5). If amplification at Ca did not allow for detection of a specific locus, PCR was repeated with 40 cycles (Table 5). All six loci were detected in the five samples from the treated plot. B. brongniartii genotype I, i.e., the applied BCA strain, was detected in four of the five soil samples, and genotype II was detected in sample T5 (Table 5). Among the samples from the control plot, only sample C2 yielded PCR products for each SSR locus. The resulting fingerprint corresponded to genotype III. Even though alleles corresponding to four loci of genotype III were detected in soil sample C3, the fingerprint remained incomplete and no genotype was assigned. In soil sample C4, only the allele at locus Bb8D6, which was common to all three genotypes, was detected, while for locus Bb4H9 an allele with the size of 215 bp, which was different from the corresponding alleles of any of the three genotypes isolated, was observed. None of the loci were detected in samples C1 and C5.


arrow
DISCUSSION
 
The goal of this study was to assess the feasibility of cultivation-independent multilocus SSR genotyping of fungal strains in bulk soil DNA extracts. The ascomycete fungus B. brongniartii, used in biological control of the European cockchafer, M. melolontha, served as a model system to develop a generally applicable strategy. A BCA strain applied in a field experiment was monitored by this strategy, and the results were validated by comparison with those of the established cultivation-dependent approach.

Specificity of SSR detection for reliable cultivation-independent identification of specific fungal isolates from complex samples was achieved by combined use of two criteria: species specificity of SSR PCR primers and multilocus SSR fingerprinting. Species specificity of the six B. brongniartii SSR primer pairs was demonstrated by the presence of characteristic SSR amplification products from the target species and their absence from nontargets, respectively (Table 1). Species specificity for SSR primers has also been reported for other fungi (3, 39, 46). However, there are also examples of either unspecific SSR primers, which detect various species (22, 25), or highly specific primers, limited to certain strains only (12). Therefore, detection specificity of SSR primers needs to be validated prior to cultivation-independent application to complex DNA samples.

Multilocus SSR fingerprinting of B. brongniartii has been reported to discriminate individuals in natural populations with high probabilities of 92 to 99% (16). Five of the six markers used have been reported to be highly polymorphic, while one marker (Bb8D6) was not (15). In the present study, amplification from locus Bb8D6 yielded a nontarget amplification product from genomic DNA of B. bassiana, which was in accordance with findings by Enkerli et al. (15). However, with a length of 163 bp, this allele was shorter than any allele recorded for this locus from B. brongniartii (172 to 190 bp) by others (15, 16) or in the present study. The absence of any unexpected allele or unspecific amplification products in the spiking experiments (Tables 3 and 4) further confirmed specificity of the six SSR primers if applied for detection in bulk soil DNA extracts. In addition, data from the experimental field plot indicated specificity, as they revealed the same genotypes for both analyses (Table 5). The allele of 215 bp derived from locus Bb4H9 in soil sample C4 was the only one among 60 analyses that could not be attributed to the three genotypes detected (Table 5) and may indicate the presence of a fourth genotype at a very low abundance. All together, these data demonstrated that specificity of B. brongniartii SSR PCR primers is also retained in highly complex bulk soil DNA. Specificities of fungal SSR primers within plant DNA extracts have been reported previously (20, 34, 46), but to our knowledge the present study is the first report on SSR species specificity in bulk soil DNA.

Adjustment of detection sensitivities for multiple SSR loci needs to account both for template quantities in bulk soil DNA extracts and for locus-specific amplification efficiencies. Due to high sequence diversity related to the large numbers of different organisms present in a soil sample, typically, template DNA of individual genotypes is relatively nonabundant in bulk soil DNA (31). Sample-specific template quantities were accounted for by using Ca numbers, which also adjusted for primer-specific detection sensitivities. Ca numbers were set as low as possible in order to minimize the risk of PCR biases and artifact generation. For the 10 soil samples, four classes of Ca were sufficient to cover the range of all 60 CT values. This allowed for efficient detection of all markers in all samples. Resulting quantities of all PCR products were similar; thus, no individual dilutions were necessary prior to fragment sizing. The observed reproducibility of CT-rel values both in genomic DNA and in the tested bulk soil DNA extracts indicated a general stability of SSR marker detection sensitivities for the B. brongniartii system.

Detection limits for reproducible cultivation-independent genotyping of B. brongniartii were estimated by analyzing either spiked-soil DNA or field soil samples. Unambiguous genotype identification from spiked-soil DNA was possible when 50 ng of bulk soil DNA was spiked with 2 pg genomic DNA of B. brongniartii but failed for assays with soil spiked with 0.2 pg genomic DNA (Table 4). Because in some reactions alleles were also amplified when present at quantities of 0.6 pg (locus Bb8D6 in mixture e) or 0.2 pg (loci Bb1F4 and Bb5F4 in mixture b and locus Bb4H9 in mixture e), the actual detection limit for B. brongniartii may be between 0.2 and 2 pg genomic DNA (Table 4). These quantities equal 4.5 or 45 genome copies, respectively, if assuming a genome size of 40 Mbp, as determined for the closest relative, B. bassiana (38). A similar detection limit of 26 copies per PCR has been reported for Trichoderma atroviride (11). For field soil samples, the detection limit of the cultivation-independent analysis of B. brongniartii genotypes depended on unambiguous identification of the least efficiently amplifying locus, Bb2A3, processed at a maximum of 40 PCR cycles (Table 5). The resulting detection limit corresponded to approximately 104 CFU g–1 (dry weight) soil (Table 5, sample T3). Similar cultivation-independent detection limits were reported for Metarhizium anisopliae, 4 x 104 CFU g–1 (dry weight) soil (17), Fusarium solani, 1 x 104 CFU g–1 (dry weight) soil (18), and Paecilomyces lilacinus, 3 x 103 CFU g–1 (dry weight) soil (2). With a mean of 275 µg DNA g–1 (dry weight) soil, the 50 ng DNA used for PCR corresponded to 0.18 mg soil. Thus, the 104 CFU g–1 (dry weight) would represent approximately 2 CFU per PCR. With such low template quantities, stochastic PCR amplification will provide unreliable results (45). However, 1 CFU may represent conidia, as well as mycelium carrying more than one nucleus (10). In addition, cultivation detects only viable material, whereas cultivation-independent analysis also detects target sequences from unculturable and possibly dead cells (31). For B. brongniartii, the relation between the detected CFU and the number of conidia added to soil was previously estimated to be 1:20; thus, 2 CFU may represent approximately 40 conidia (27). This almost perfectly supports the observed detection limit of 104 CFU g–1 (dry weight), corresponding to about 40 genome copies per PCR. These considerations are in agreement with the 2 pg detection limit for genomic DNA (Table 4). The use of a 100-times-higher quantity of soil, i.e., 20 mg per analysis, for plate counting resulted in a 100-times-higher sensitivity for B. brongniartii. This allowed detection of B. brongniartii at densities of 261 and 816 CFU g–1 (dry weight) in soil samples C3 and C5, respectively, which were not detectable with the cultivation-independent analysis (Table 5).

Cultivation-independent multilocus genotyping is an attractive alternative for B. brongniartii monitoring. The method has a detection limit of about 104 CFU g–1 (dry weight) of B. brongniartii as required to induce epizootics in M. melolontha-infested fields (27). In addition, it allows for substantial reduction of the time and cost for BCA monitoring. Analyses can be performed within 1 week, whereas the cultivation-dependent approach may require up to 2 weeks for density analysis and approximately 6 weeks for genotyping due to cultivation and subsequent DNA extraction (16). Furthermore, the method allowed monitoring of multiple cooccurring strains spiked into bulk soil DNA (Table 4). This can be important for fields where genotypic diversity may be high, e.g., 22 different B. brongniartii genotypes in a plot of 400 m2 (J. Enkerli, unpublished data). As only one of the three occurring genotypes was detected per field soil sample (Table 5), spiking bulk soil DNA with three different genotypes per sample may cover the expected range of genotype diversity and may represent a realistic model (Table 4).

The three genotypes detected in the field experiment were unevenly distributed between the treated and the control plot (Table 5), which was in accordance with other studies revealing generally patchy distributions of soil fungi on small scales (8, 33, 36). The high plate counts caused by indigenous strains (Table 4, soil samples T5 and C2) emphasized the need for genotypic analyses when monitoring applied BCA strains in order to avoid false conclusions.

With a growing need to assess potential risks associated with the release of BCAs into the environment (24), effective and efficient monitoring becomes increasingly important (4). The cultivation-independent monitoring approach based on multiple SSRs combines species-specific detection of polymorphic markers with strain-level resolution. This allows detection of both BCA and indigenous strains of a target species. Furthermore, this approach will allow for genetic analyses of other organisms (2, 9, 11) as well as profiling of microbial community structures within the same DNA extract (21, 42). Cultivation-independent fingerprinting using SSR thus could ideally be used to study interactions between released fungal strains and indigenous soil microbial communities.


arrow
ACKNOWLEDGMENTS
 
We thank S. Keller and C. Schweizer for providing access to the field experiment and technical support for cultivation-dependent analyses.

This research project was supported by funding received from the Swiss Federal Office for the Environment (FOEN) within its Research Program on Biosafety in Nonhuman Genetic Engineering.


arrow
FOOTNOTES
 
* Corresponding author. Mailing address: Molecular Ecology, Agroscope Reckenholz-Tänikon Research Station ART, Reckenholzstrasse 191, 8046 Zürich, Switzerland. Phone: 41 (0)44 377 72 06. Fax: 41 (0)44 377 72 01. E-mail: juerg.enkerli{at}art.admin.ch Back

{triangledown} Published ahead of print on 24 August 2007. Back


arrow
REFERENCES
 
    1
  1. Anderson, I. C., and J. W. Cairney. 2004. Diversity and ecology of soil fungal communities: increased understanding through the application of molecular techniques. Environ. Microbiol. 6:769-779.[CrossRef][Medline]
    2. 2
  2. Atkins, S. D., I. M. Clark, S. Pande, P. R. Hirsch, and B. R. Kerry. 2005. The use of real-time PCR and species-specific primers for the identification and monitoring of Paecilomyces lilacinus. FEMS Microbiol. Ecol. 51:257-264.[CrossRef][Medline]
    3. 3
  3. Barres, B., C. Dutech, A. Andrieux, H. Caron, J. Pinon, and P. Frey. 2006. Isolation and characterization of 15 microsatellite loci in the poplar rust fungus, Melampsora larici-populina, and cross-amplification in related species. Mol. Ecol. Notes 6:60-64.[CrossRef]
    4. 4
  4. Bidochka, M. J. 2001. Monitoring the fate of biocontrol fungi, p. 193-218. In T. M. Butt, C. W. Jackson, and N. Magan (ed.), Fungi as biocontrol agents. CABI Publishing, Oxon, United Kingdom.
    5. 5
  5. Breuillin, F., C. Dutech, and C. Robin. 2006. Genetic diversity of the chestnut blight fungus Cryphonectria parasitica in four French populations assessed by microsatellite markers. Mycol. Res. 110:288-296.[CrossRef][Medline]
    6. 6
  6. Bundt, M., F. Widmer, M. Pesaro, J. Zeyer, and P. Blaser. 2001. Preferential flow paths: biological ‘hot spots’ in soils. Soil Biol. Biochem. 33:729-738.[CrossRef]
    7. 7
  7. Bustin, S. A. 2004. A-Z of quantitative PCR. IUL Press, San Diego, CA.
    8. 8
  8. Cairney, J. W. G. 2005. Basidiomycete mycelia in forest soils: dimensions, dynamics and roles in nutrient distribution. Mycol. Res. 109:7-20.[CrossRef][Medline]
    9. 9
  9. Castrillo, L. A., L. Thomsena, P. Junejaa, and A. E. Hajeka. 2007. Detection and quantification of Entomophaga maimaiga resting spores in forest soil using real-time PCR. Mycol. Res. 111:324-331.[CrossRef][Medline]
    10. 10
  10. Castrillo, L. A., J. D. Vandenberg, and S. P. Wraight. 2003. Strain-specific detection of introduced Beauveria bassiana in agricultural fields by use of sequence-characterized amplified region markers. J. Invertebr. Pathol. 82:75-83.[CrossRef][Medline]
    11. 11
  11. Cordier, C., V. Edel-Hermann, F. Martin-Laurent, B. Blala, C. Steinberg, and C. Alabouvette. 2007. SCAR-based real time PCR to identify a biocontrol strain (T1) of Trichoderma atroviride and study its population dynamics in soils. J. Microbiol. Methods 68:60-68.[CrossRef][Medline]
    12. 12
  12. Dalleau-Clouet, C., N. Gauthier, A. M. Risterucci, M. C. Bon, and J. Fargues. 2005. Isolation and characterization of microsatellite loci from the entomopathogenic hyphomycete Paecilomyces fumosoroseus. Mol. Ecol. Notes 5:496-498.[CrossRef]
    13. 13
  13. Dauch, A. L., A. K. Watson, and S. H. Jabaji-Hare. 2003. Detection of the biocontrol agent Colletotrichum coccodes (183088) from the target weed velvetleaf and from soil by strain-specific PCR markers. J. Microbiol. Methods 55:51-64.[CrossRef][Medline]
    14. 14
  14. Dodd, S. L., R. A. Hill, and A. Stewart. 2004. A duplex-PCR bioassay to detect a Trichoderma virens biocontrol isolate in non-sterile soil. Soil Biol. Biochem. 36:1955-1965.[CrossRef]
    15. 15
  15. Enkerli, J., F. Widmer, C. Gessler, and S. Keller. 2001. Strain-specific microsatellite markers in the entomopathogenic fungus Beauveria brongniartii. Mycol. Res. 105:1079-1087.
    16. 16
  16. Enkerli, J., F. Widmer, and S. Keller. 2004. Long-term field persistence of Beauveria brongniartii strains applied as biocontrol agents against European cockchafer larvae in Switzerland. Biol. Control 29:115-123.[CrossRef]
    17. 17
  17. Entz, S. C., D. L. Johnson, and L. M. Kawchuk. 2005. Development of a PCR-based diagnostic assay for the specific detection of the entomopathogenic fungus Metarhizium anisopliae var. acridum. Mycol. Res. 109:1302-1312.[CrossRef][Medline]
    18. 18
  18. Filion, M., M. St.-Arnaud, and S. H. Jabaji-Hare. 2003. Direct quantification of fungal DNA from soil substrate using real-time PCR. J. Microbiol. Methods 53:67-76.[CrossRef][Medline]
    19. 19
  19. Giovannoni, S. J., E. F. Delong, G. J. Olsen, and N. R. Pace. 1988. Phylogenetic group-specific oligodeoxynucleotide probes for identification of single microbial cells. J. Bacteriol. 170:720-726.[Abstract/Free Full Text]
    20. 20
  20. Gobbin, D., I. Pertot, and C. Gessler. 2003. Identification of microsatellite markers for Plasmopara viticola and establishment of high throughput method for SSR analysis. Eur. J. Plant Pathol. 109:153-164.[CrossRef]
    21. 21
  21. Hartmann, M., B. Frey, R. Kölliker, and F. Widmer. 2005. Semi-automated genetic analyses of soil microbial communities: comparison of T-RFLP and RISA based on descriptive and discriminative statistical approaches. J. Microbiol. Methods 61:249-360.
    22. 22
  22. Hayden, H. L., L. M. Wilson, A. J. Cozijnsen, and B. J. Howlett. 2004. Characterization and cross-species amplification of microsatellite loci in the plant pathogenic fungus Leptosphaeria maculans. Mol. Ecol. Notes 4:480-481.[CrossRef]
    23. 23
  23. Hermosa, M. R., I. Grondona, J. M. Diaz-Minguez, E. A. Iturriaga, and E. Monte. 2001. Development of a strain-specific SCAR marker for the detection of Trichoderma atroviride 11, a biological control agent against soilborne fungal plant pathogens. Curr. Genet. 38:343-350.[CrossRef][Medline]
    24. 24
  24. Hokkanen, H. M. T., F. Bigler, G. Burgio, J. C. van Lenteren, and M. B. Thomas. 2003. Ecological risk assessment framework for biological control agents, p. 1-14. In H. M. T. Hokkanen (ed.), Environmental impacts of microbial insecticides. Kluwer Academic Publishers, Dordrecht, The Netherlands.
    25. 25
  25. Hosid, E., I. Grishkan, Z. Frenkel, S. P. Wasser, E. Nevo, and A. Korol. 2005. Microsatellite markers for assessing DNA polymorphism of Emericella nidulans in nature. Mol. Ecol. Notes 5:647-649.[CrossRef]
    26. 26
  26. Keller, L., and M. J. Bidochka. 1998. Habitat and temporal differences among soil microfungal assemblages in Ontario. Can. J. Bot. 76:1798-1805.[CrossRef]
    27. 27
  27. Keller, S., P. Kessler, D. B. Jensen, and C. Schweizer. 2002. How many spores of Beauveria brongniartii are needed to control Melolontha melolontha. IOBC/WPRS Bull. 25:59-64.
    28. 28
  28. Keller, S., P. Kessler, and C. Schweizer. 2003. Distribution of insect pathogenic soil fungi in Switzerland with special reference to Beauveria brongniartii and Metarhizium anisopliae. Biocontrol 48:307-319.[CrossRef]
    29. 29
  29. Kessler, P., J. Enkerli, C. Schweizer, and S. Keller. 2004. Survival of Beauveria brongniartii in the soil after application as a biocontrol agent against the European cockchafer Melolontha melolontha. Biocontrol 49:563-581.[CrossRef]
    30. 30
  30. Kessler, P., H. Matzke, and S. Keller. 2003. The effect of application time and soil factors on the occurrence of Beauveria brongniartii applied as a biological control agent in soil. J. Invertebr. Pathol. 84:15-23.[CrossRef][Medline]
    31. 31
  31. Kirk, J., L. A. Beaudette, M. Hart, P. Moutoglis, J. N. Klironomos, H. Lee, and J. T. Trevors. 2004. Methods of studying soil microbial diversity. J. Microbiol. Methods 58:169-188.[CrossRef][Medline]
    32. 32
  32. Kreader, C. 1996. Relief of amplification inhibition in PCR with bovine serum albumin or T4 gene 32 protein. Appl. Environ. Microbiol. 62:1102-1106.[Abstract]
    33. 33
  33. Meyling, N. V., and J. Eilenberg. 2006. Occurrence and distribution of soil borne entomopathogenic fungi within a single organic agroecosystem. Agric. Ecosyst. Environ. 113:336-341.[CrossRef]
    34. 34
  34. Naef, A., M. Senatore, and G. Defago. 2006. A microsatellite based method for quantification of fungi in decomposing plant material elucidates the role of Fusarium graminearum DON production in the saprophytic competition with Trichoderma atroviride in maize tissue microcosms. FEMS Microbiol. Ecol. 55:211-220.[CrossRef][Medline]
    35. 35
  35. Nahar, P., V. Ghormade, and M. V. Deshpande. 2004. The extracellular constitutive production of chitin deacetylase in Metarhizium anisopliae: possible edge to entomopathogenic fungi in the biological control of insect pests. J. Invertebr. Pathol. 85:80-88.[CrossRef][Medline]
    36. 36
  36. Oros-Sichler, M., N. C. M. Gomes, G. Neuber, and K. Smalla. 2006. A new semi-nested PCR protocol to amplify large 18S rRNA gene fragments for PCR-DGGE analysis of soil fungal communities. J. Microbiol. Methods 65:63-75.[CrossRef][Medline]
    37. 37
  37. Papierok, B., and A. E. Hajek. 1997. Fungi: Entomophthorales, p. 187-212. In L. A. Lacey (ed.), Manual of techniques in insect pathology. Academic Press, San Diego, CA.
    38. 38
  38. Pfeifer, T., and G. Khachatourians. 1993. Electrophoretic karyotype of the entomopathogenic deuteromycete Beauveria bassiana. J. Invertebr. Pathol. 61:231-235.[CrossRef]
    39. 39
  39. Prospero, S., J. A. Black, and L. M. Winton. 2004. Isolation and characterization of microsatellite markers in Phytophthora ramorum, the causal agent of sudden oak death. Mol. Ecol. Notes 4:672-674.[CrossRef]
    40. 40
  40. Ratcliff, A. W., M. D. Busse, and C. J. Shestak. 2006. Changes in microbial community structure following herbicide (glyphosate) additions to forest soils. Appl. Soil Ecol. 34:114-124.[CrossRef]
    41. 41
  41. Riba, G., and A. M. Ravelojoana. 1984. The parasexual cycle in the entomopathogenic fungus Paecilomyces fumoso-roseus (Wize) Brown and Smith. Can. J. Microbiol. 30:922-926.
    42. 42
  42. Schwarzenbach, K., J. Enkerli, and F. Widmer. 2007. Objective criteria to assess representativity of soil fungal community profiles. J. Microbiol. Methods 68:358-366.[CrossRef][Medline]
    43. 43
  43. Strasser, H., A. Forer, and F. Schinner. 1996. Development of media for the selective isolation and maintenance of virulence of Beauveria brongniartii, p. 125-130. In T. A. Jackson and T. R. Glare (ed.), Microbial control of soil dwelling pests. AgResearch, Lincoln, New Zealand.
    44. 44
  44. Stukenbrock, E. H., S. Banke, and B. A. McDonald. 2006. Global migration patterns in the fungal wheat pathogen Phaeosphaeria nodorum. Mol. Ecol. 15:2895-2904.[Medline]
    45. 45
  45. Widmer, F., R. J. Seidler, and L. S. Watrud. 1996. Sensitive detection of transgenic plant marker gene persistence in soil microcosms. Mol. Ecol. 5:603-613.
    46. 46
  46. Zhou, Z. H., M. Miwa, Y. Matsuda, and T. Hogetsu. 2001. Spatial distribution of the subterranean mycelia and ectomycorrhizae of Suillus grevillei genets. J. Plant Res. 114:179-185.[CrossRef]

Applied and Environmental Microbiology, October 2007, p. 6519-6525, Vol. 73, No. 20
0099-2240/07/$08.00+0     doi:10.1128/AEM.01405-07
Copyright © 2007, American Society for Microbiology. All Rights Reserved.




This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowReprints and Permissions
Right arrow Copyright Information
Right arrow Books from ASM Press
Right arrow MicrobeWorld
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Schwarzenbach, K.
Right arrow Articles by Enkerli, J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Schwarzenbach, K.
Right arrow Articles by Enkerli, J.
Agricola
Right arrow Articles by Schwarzenbach, K.
Right arrow Articles by Enkerli, J.

Copyright © 2009 by the American Society for Microbiology.   For an alternate route to Journals.ASM.org, visit: http://intl-journals.asm.org | More Info»