Mycorrhiza DOI 10.1007/s00572-014-0602-7
ORIGINAL PAPER
Quantification of arbuscular mycorrhizal fungal DNA in roots: how important is material preservation? Martina Janoušková & David Püschel & Martina Hujslová & Renata Slavíková & Jan Jansa
Received: 30 May 2014 / Accepted: 21 August 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Monitoring populations of arbuscular mycorrhizal fungi (AMF) in roots is a pre-requisite for improving our understanding of AMF ecology and functioning of the symbiosis in natural conditions. Among other approaches, quantification of fungal DNA in plant tissues by quantitative realtime PCR is one of the advanced techniques with a great potential to process large numbers of samples and to deliver truly quantitative information. Its application potential would greatly increase if the samples could be preserved by drying, but little is currently known about the feasibility and reliability of fungal DNA quantification from dry plant material. We addressed this question by comparing quantification results based on dry root material to those obtained from deep-frozen roots of Medicago truncatula colonized with Rhizophagus sp. The fungal DNA was well conserved in the dry root samples with overall fungal DNA levels in the extracts comparable with those determined in extracts of frozen roots. There was, however, no correlation between the quantitative data sets obtained from the two types of material, and data from dry roots were more variable. Based on these results, we recommend dry material for qualitative screenings but advocate using frozen root materials if precise quantification of fungal DNA is required.
Electronic supplementary material The online version of this article (doi:10.1007/s00572-014-0602-7) contains supplementary material, which is available to authorized users. M. Janoušková : D. Püschel : M. Hujslová : R. Slavíková : J. Jansa Institute of Microbiology, Academy of Sciences of the Czech Republic, Vídeňská 1083, 142 20 Praha 4 – Krč, Czech Republic M. Janoušková (*) : D. Püschel Institute of Botany, Academy of Sciences of the Czech Republic, Zámek 1, 252 43 Průhonice, Czech Republic e-mail: [email protected]
Keywords Arbuscular mycorrhizal fungi . Intraradical colonization . PCR inhibition . Quantitative real-time PCR (qPCR) . Sample preservation
Introduction Many fungal groups colonize living plant tissues and form mutualistic, parasitic, or neutral relationships with plants. Monitoring their populations is vital for plant protection in the case of pathogenic fungi and important for improving our understanding of basic ecological questions in the case of other fungal groups. Communities of obligatory biotrophic arbuscular mycorrhizal fungi (AMF), for example, importantly influence the productivity and diversity of plant communities as well as nutrient and energy fluxes between plants and the soil system (van der Heijden et al. 1998; Smith and Read 2008). The intraradical structures of AMF do not enable reliable microscopic discrimination of species while communities of soil-borne spores with diagnostic morphological features do not reflect the diversity of AMF symbionts actually interacting with plants. Rising interest in AMF communities goes therefore hand in hand with development of DNA-based tools, which have become indispensable in AMF research. DNAbased techniques enabled discovering new aspects of AM symbiosis such as high hidden diversity of AMF (Clapp et al. 1995; Öpik et al. 2009; Sanders et al. 1996) or specific interactions between certain plant and AMF taxa (Davison et al. 2011; Gollotte et al. 2004; Helgason et al. 2002). With current scientific questions going deeper into AMF community ecology, high throughput techniques are required to process large numbers of samples. Here, quantitative realtime PCR (qPCR) with taxon-specific primers and/or probes is gaining increasing attention (Alkan et al. 2006; Janoušková et al. 2013; Jansa et al. 2008; Jansa et al. 2014; Thonar et al.
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2012; Thonar et al. 2014; Wagg et al. 2011). It is currently the only approach enabling, at the same time, discrimination and precise quantification of specific sequence motifs in roots colonized by multiple AMF taxa. In comparison with merely qualitative tools such as construction of sequence libraries, terminal restriction fragment length polymorphism, or other fingerprinting methods, its main advantage is in recording subtle shifts in relative abundances of the individual taxa besides their presence/absence (Thonar et al. 2014). The application of qPCR in community research of mycorrhizal and other endophytic fungi is however still in its beginning as evident from comparison with the field of fungal phytopathology, where qPCR, after two decades of basic research, is becoming a routine tool of early pathogen detection (Sanzani et al. 2014). Analogically, qPCR could become an alternative technique to subjectivity-prone microscopy for determining the overall abundance of non-pathogenic fungi in plant tissues, profiting from its high throughput and reproducibility. DNA-based methods impose certain requirements on sample preservation, which have to be balanced with other requirements or limitations of a study setup. Specifically, deepfreezing is without doubt the best choice for the preservation of biomolecules including DNA, but drying or chemical conservation is more convenient and often the only possible approach when sampling takes place far away from appropriately equipped laboratories. Both alternative approaches have been successfully applied to material used for AMF community analyses by sequencing of amplified fragments of ribosomal DNA, e.g., by Alguacil et al. (2008), Cesaro et al. (2008), and Öpik et al. (2003). On the other hand, poor amplification of AMF DNA from dry root material has been reported, and more rapid degradation of AMF DNA due to the drying process has been suggested, as compared to plant DNA (Bainard et al. 2010). Quantitative data are more sensitive to bias by low quality of DNA extracts such as presence of inhibitors or DNA fragmentation (Bustin 2004). For this reason, studies utilizing qPCR for fungal detection predominantly rely on fresh material or on cryogenic sample preservation. However, if drying proved sufficient as a sample conservation approach, it would greatly broaden the application potential of fungal quantification by qPCR. For instance, it would enable evaluation of samples from remote areas, which are highly underrepresented in microbial diversity studies as demonstrated for AMF by Öpik et al. (2010). Furthermore, the use of dry material could have important advantages in processing of experimental samples as it would facilitate representative sampling. High spatial heterogeneity of AMF nuclei in their intraradical structures is difficult to account for by sampling fresh segments from the entire root system (Gamper et al. 2008). Homogenization of larger amounts of roots, easy to achieve by milling of dry samples, could greatly increase the representativeness of sampling.
There is however no information on whether dry material can render reliable qPCR data on AMF abundance in plant tissues. We therefore focused on the feasibility and reliability of quantification of AMF DNA from dry root powder as alternative to frozen root material. We compared root material of different ages to account for dynamics of the fungal DNA levels in roots (Jansa et al. 2008; Krak et al. 2012; Thonar 2009) and potential effects of plant age on the quality of DNA extracts. We designed our experiments to answer the following main questions: (1) Does qPCR on DNA extracts from dry roots produce the same results as on DNA extracts from frozen samples? (2) Can the use of dry root powder, in comparison to frozen roots, decrease the variability of qPCR measurements?
Material and methods Material preparation Seeds of Medicago truncatula Gaertn. J5 were soaked for 7 min in 96 % H2SO4, and pre-germinated for 2 days on a moist filter paper. Cultivation substrate was prepared by mixing autoclaved sand (45 %), autoclaved zeolite (45 %), and γ-sterilized silty-clay soil (10 %), which had the following main characteristics: pH (water)=8.9, total P 46 mg kg−1, water-extractable P 2.6 mg kg−1, total N 0.13 g kg−1, and organic C 2.2 g kg−1. Fifteen pots (volume 2 L, height 21 cm) were filled with the cultivation substrate, which was amended with 5 % (v:v) of inoculum of the arbuscular mycorrhizal fungus Rhizophagus sp. “Chomutov” (formerly Glomus intraradices “Chomutov”); for origin and cultivation history of this isolate, see Krak et al. (2012). The inoculum was prepared by air-drying and homogenization of the substrate of a one-year-old culture of this AMF isolate on maize and Desmodium sp. and contained chopped roots, extraradical mycelium and spores in the original cultivation substrate. Two pre-germinated seeds were planted into each pot, and non-vital seedlings were replaced after 1 week. The seedlings were inoculated at planting with 1 ml of suspension of Sinorhizobium meliloti isolate number 1021 from INRA Toulouse. The bacterial inoculum was prepared by cultivation in tryptone-yeast extract broth for 2 days and subsequent washing with 0.5 % MgSO4. The plants were cultivated in a greenhouse (14 h photoperiod) with supplemental metal halide discharge lamps (min. 8 klux) and fertilized once per week with 100 ml of P2N3 solution (Gryndler et al. 1992) with P concentration in the nutrient solution reduced to 20 μM. The pots were harvested after 57 (harvest 1), 68 (harvest 2), and 90 (harvest 3) days of cultivation, five pots per harvest. The root systems of the plants were carefully lifted from the pots, washed, dried in paper tissue, and stretched out. The
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upper 5 cm of the root systems were removed, and the roots from the depths of approximately 5–15 cm were used for sampling. The roots were cut to fragments of about 2 cm in length. Five samples of 100 mg fresh weight were collected by randomly picking root segments, immediately frozen in liquid nitrogen, and stored at −80 °C for molecular quantification of fungal DNA. A sample of about 500 mg root fresh weight was collected in the same way for microscopic determination of root colonization and stored in 50 % ethanol. The rest of this part of the root system was dried at 60 °C, pulverized in a ball mill (Retsch MM 200, Haan, Germany; 25 Hz, 2 min), and stored dry at room temperature for 3–4 months before DNA extraction. The extent of root length colonized by fungal structures was determined after trypan blue staining (Koske and Gemma 1989) using the magnified intersection method (McGonigle et al. 1990). Fifty root intersects were scored per sample. No attempt was made to distinguish intraradical spores from vesicles as this cannot be done with certainty on trypan bluestained roots. DNA extraction and characterization of the extracts DNA was extracted from the deep-frozen and dried root samples using two DNA extraction approaches resulting in a total of four combinations of material × DNA extraction method (extraction treatments). DNeasy Plant Mini Kit (QIAGEN, Hilden, Germany) was chosen as one DNA extraction approach and performed according to the manufacturer’s instructions, the glassmilk method described by Gryndler et al. (2013) as the other. Briefly, after incubation of homogenized plant material in CTAB extraction buffer, the extracts were purified by chloroform and combined with the bind buffer (saturated NaCl with 10 mM Bis-Tris, pH 6.0) and 50 % glassmilk (water suspension of acid-washed silicon dioxide). After centrifugation, washing, and drying of the pellet, it was resuspended and centrifuged again to transfer the extracted DNA into solution and separate it from the silicon dioxide particles. Aliquots of 100 mg of frozen roots were thoroughly homogenized using liquid nitrogen and a mortar and pestle for both DNA extraction methods. The dry root powder was weighted to 20 mg or 10 mg for the kit or the glassmilk extraction method, respectively, and thoroughly vortexed with the appropriate lysis buffer. The kit-extracted DNA was eluted with 80 μl of 10 mM Tris-HCl buffer (pH 7.5); the glassmilkextracted DNA was resuspended in 50 μl of 10 mM TrisEDTA (TE) buffer (pH 7.5). All DNA extracts were stored at −80 °C until use. Experimental treatments and numbers of extractions processed per root system are summarized in Table 1. DNA concentration in the extracts was determined spectrophotometrically using NanoDrop 1000 Spectrophotometer
(Thermo Scientific, Waltham, USA) and fluorometrically using Quant-iT PicoGreen® dsDNA Assay Kit (Invitrogen, Carlsbad, USA) and Infinite M200 microplate reader (Tecan, Männedorf, Switzerland). As correlation between these two measurements was poor and spectrophotometry substantially overestimated DNA concentrations in nearly all treatments (except in the kit extracts from frozen material), the values determined by PicoGreen fluorescence were used in all subsequent calculations. The DNA yield of the extractions (amount of extracted DNA per sample) was calculated to ng DNA mg−1 of root dry weight. The average coefficient of dry to fresh root weight obtained from all harvested root systems was used for the calculation of root dry weight of the frozen samples. The integrity of the extracted DNA was visually assessed after electrophoresis of the DNA extracts in 1 % agarose gel with ethidium bromide. qPCR experiments The following experiments were conducted: (1) Evaluation of the effect of material and DNA extraction method on PCR inhibition by the DNA extracts. This was determined using one extract per root system and extraction treatment, i.e., on 60 extracts in total. All DNA extracts were measured at tenfold dilution; extracts from harvests 1 and 3 also at two- and fivefold dilutions. (2) Evaluation of the effect of material and DNA extraction method on AMF mitochondrial ribosomal DNA (mtDNA) copy numbers in the DNA extracts. This evaluation was based on the same set of extracts as the experiment 1; all extracts were measured at tenfold dilution only. (3) Comparison of the variability of PCR inhibition by the DNA extracts within root system between DNA extracts from frozen and dry root materials. This was determined on 3 kit extracts were used for the determination extracts per root system and material including only samples from harvests 1 and 3, i.e., on 60 extracts in total. The extracts were measured at tenfold dilution only. (4) Comparison of the variability of AMF mtDNA copy numbers within root system between DNA extracts from frozen and dry root samples. This evaluation was based on the same set of extracts as the experiment 3 (at tenfold dilution). The qPCRs were performed in StepOnePlus instrument (Applied Biosystems, Foster City, USA). The PCR mix (total volume 20 μl) contained 1x HOT FIREPol® Probe qPCR Mix Plus with ROX reference dye (Solis BioDyne, Tartu, Estonia), 0.5 μM each primer, 0.125 μM probe, and 2 μl of template. Each sample was ran in technical duplicates or triplicates, which were averaged for all further calculations. Inhibition of qPCR by the DNA extracts was tested by determining the recovery of known amounts of internal DNA standard (IS) in the presence of the DNA extracts. The IS— linearized plasmid carrying a fragment of cassava mosaic virus (GenBank accession AJ4279140)—was added into PCR reactions in the amount of 2×106 copy numbers per
Mycorrhiza Table 1 Numbers of samples extracted per root system from dry or frozen materials using either QIAGEN DNeasy Plant Mini Kit (kit) or the glassmilk method (Gryndler et al. 2013). Five replicate root systems were extracted per harvest
Material
Extraction method
Frozen
Kit Glassmilk Kit Glassmilk
Dry Total
Total×5 root systems
reaction in 10 mM TE buffer (pH 7.5). The IS was then quantified using the assay of Thonar et al. (2012): forward primer 5′-CGAACCTGGACTGTTATGATG-3′, reverse primer 5′-AATAAACAATCCCCTGTATTTCAC-3′, TaqMan probe FAM-CACCAGGCACCAACAACGACCATTBHQ1. The DNA extracts were added in the amount of 2 μl, diluted as specified above. The reaction conditions were as follows: initial denaturation for 15 min at 95 °C followed by 45 cycles of denaturation (95 °C, 10 s), annealing (50 °C, 20 s), and extension (72 °C, 10 s). Mitochondrial large ribosomal subunit gene (mtDNA) of Rhizophagus sp. was quantified as described previously by Kiers et al. (2011, assay for G. intraradices) using the following primers: forward primer 5′-TTTTAGCGATAGCGTAAC AGC-3′, reverse primer 5′-TACATCTAGGACAGGGTTTC G-3′, and TaqMan probe FAM-AAACTGCCACTCCCTC CATATCCAA-BHQ1. The reaction conditions were initial denaturation for 15 min at 95 °C followed by 45 cycles of denaturation (95 °C, 10 s), annealing (54 °C, 1 min), and extension (72 °C, 10 s). Threshold cycle (Ct) values were converted to copy numbers (CN) μl−1 of template using standard curves previously established under the same cycling conditions as described above. The standard curve for the IS assay was based on fivefold dilutions of the linearized plasmid spanning the concentration from 109 to 20 copies μl−1 template. It was constructed by plotting the Ct values against logarithmically transformed concentrations. The equation of the standard curve was y=−3.595x+43.327 (R2 =0.9997) where x = log copies μl−1 template and y=Ct. Recovery of the IS was calculated as R(%)=CNsample/CNblank ×100, where CNsample stands for the copy numbers of IS determined in the corresponding sample, and CNblank for the copy numbers determined in control samples ran on the same plate with ddH2O added to the reaction mix instead of DNA extract. The standard curve for the Rhizophagus sp. assay was constructed with a fourfold serial dilution series of linearized plasmid containing the respective amplicon (1011−1.3 104 CN μl−1). The resulting equation was y=−3.700x+48.837 (R2 = 0.9952). The copy numbers per μl template were converted to CN ng−1 extracted DNA using the sample-specific DNA concentrations determined by PicoGreen fluorescence. These values were corrected by sample-specific IS recovery for the
Harvest 1 (57 days)
Harvest 2 (68 days)
Harvest 3 (90 days)
3 1 3 1 8
1 1 1 1 4
3 1 3 1 8
40
20
40
respective template dilution to account for differences in PCR inhibition among samples, i.e., they were calculated to values, which would have been obtained without any inhibition. Data analysis Relationships between the different data sets were tested by correlation analysis. Effects of the factors material (dry vs. frozen), extraction method (kit vs. glassmilk) and plant age on DNA yield, IS recovery, and AMF mtDNA copy numbers were assessed by three-way ANOVA or by non-parametric Kruskal-Wallis test when the data did not meet the assumptions of ANOVA. Root colonization data were evaluated by one-way ANOVA. Multiple comparisons were conducted with Tukey’s multiple comparison test. Variability among samples from one root system was expressed as a coefficient of variation (CV), which was calculated from the qPCR results of the three extracts analyzed per each root system and type of material. Effects of the factors’ material and plant age on CV were assessed by twoway ANOVA. The CV was also used to compare variability in AMF mtDNA copy numbers among root systems based on data from experiment 2. CV was calculated for each combination of extraction treatment and harvest based on values obtained for the five replicate root systems. Effects of the factors’ material and extraction procedure were assessed by two-way ANOVA regarding the three harvests as replicates within extraction treatment. All statistical analyses were carried out in Statistica 12 (StatSoft, Tulsa, USA).
Results Characteristics of the DNA extracts DNA yields of the extracts did not differ between the two materials; they were generally higher in kit extracts than in glassmilk extracts and increased with plant age (Table 2). DNA integrity visually assessed after electrophoresis in agarose gels was highest in kit extracts from frozen roots, where a
Mycorrhiza Table 2 Yields of DNA extractions from dry or frozen root materials obtained either with QIAGEN DNeasy Plant Mini Kit (kit) or using the glassmilk method (Gryndler et al. 2013) and the effect of tenfold-diluted DNA extracts on the recovery of internal DNA standard (IS) Material
Dry
Extraction method
Plant age (days)
Yield (ng DNA mg−1 RDW)
Recovery of IS (%)
Dry
Frozen
Dry
Frozen
Kit
57
174a (42)a
100a (35)y
78 (8)bc
94 (9)a
Glassmilk
68 90 57 68 90
151 (29)a 204a (17)a 94 (27)b 88 (18)b 146 (4)a Significant effects n.s. (1.2) (6.9)** (14.5)*** n.d. n.d. n.d. n.d.
215 (75)x 225a (42)x 160 (59)xy 227 (40)x 151 (21)xy
68 (8)c 61 (15)c 102 (3)a 93 (7)ab 94 (4)a
89 (7)ab 90 (6)ab 97 (2)a 97 (1)a 95 (3)a
Material (A) Extraction method (B) Plant age (C) A×B A×C B×C A×B×C
(26.1)*** (69.6)*** (6.0)** (27.6)*** n.s. (1.1) n.s. (0.2) n.s. (0.5)
Values are means of five or 15 replicates (the latter marked with a ) with s.d. in parentheses. DNA yield is based on PicoGreen fluorescence and related to root dry weight (RDW). Significant effects are given according to ANOVA (with F values in parentheses) for the parameter recovery of IS or according to Kruskal-Wallis non-parametric test (H values in parentheses) for the parameter yield. Means with the same letters are not significantly different at the threshold P≤0.05 according to Tukey’s multiple comparison test. For DNA yield, the Tukey test was conducted for each material separately in order to meet the assumption on homogeneity of variance n.s. non-significant effect (P>0.05), n.d. not determined **P≤0.01; ***P≤0.001
distinct band was apparent. In the other extracts, DNA was clearly more degraded (Online Resource, Fig. S1). DNA integrity was not visibly affected by plant age. Recovery of the IS, as an inverse measure of PCR inhibition by DNA extracts, was distinctly more affected by the presence of kit extracts from dry material as compared to the other three extraction treatments: hardly any IS could be amplified, testifying nearly total PCR inhibition, when the kit extracts from dry material were diluted only twofold, while IS recovery was at least 72 % in the presence of the other extracts at this dilution (Fig. 1). At tenfold dilution, kit extracts from dry material still caused significantly higher PCR inhibition than the other extracts. In addition, the inhibitory effect of the DNA extracts slightly but significantly increased with plant age (Table 2).
According to three-way ANOVA, AMF mtDNA copy numbers were significantly affected by material (F=6.7, P= 0.013), plant age (F=10.9, P0.05) *P≤0.05
extraction approach and added undiluted DNA extracts into their qPCRs without specifically considering PCR inhibition. This comparison highlights the need of using internal controls to exclude the negative impact of PCR inhibitors on the accuracy of qPCR detection of microorganisms in environmental samples (Schena et al. 2013). The pattern of amplification of AMF DNA from dry roots provides some support for using this approach of conserving root samples, but the discrepancy between results from frozen and dry root materials questions the reliability of the obtained data. The dynamics of AMF development found in frozen roots was characterized by a decline of AMF copy numbers in the last harvest, whereas fungal DNA as detected in extracts from dry roots remained high throughout. Neither the data
from frozen roots nor those from dry roots were however positively correlated with any of the parameters of root colonization determined microscopically (correlation was either absent or even negative). Comparability of qPCR data to microscopically determined root colonization by AMF was the main topic of the first studies focused on the qPCR as an approach to quantify development of AMF in roots and/or soil (Alkan et al. 2004; Gamper et al. 2008; Isayenkov et al. 2004). Later, it has become evident that DNA levels must be regarded as another measure of the fungal abundance, especially when root colonization of different age is evaluated, as qPCR data reflect not only the biomass but probably also the vitality of the fungal structures (Gamper et al. 2008; Jansa et al. 2008; Kiers et al. 2011; Krak et al. 2012). Furthermore, the microscopy approach employed here and in most other studies does provide only a crude approximate of fungal biomass as the intensity of
Table 5 Variability among triplicate samples from one root system expressed as coefficient of variation Material
Plant age (days)
ng DNA mg−1 RDW
Recovery of IS (%)
CN ng−1 uncorrected
CN ng−1 corrected
Dry
57 90 57 90
0.09 (0.03)b 0.08 (0.02)b 0.29 (0.10)a 0.24 (0.10)a Significant effects (31.3)***
0.07 (0.05) 0.17 (0.10) 0.07 (0.04) 0.07 (0.03)
0.15 (0.12) 0.09 (0.05) 0.22 (0.08) 0.20 (0.09)
0.17 (0.11) 0.17 (0.09) 0.19 (0.06) 0.23 (0.11)
Frozen
Material (A) Age (B) AxB
n.s. (0.6) n.s. (0.2)
n.s. (2.4) n.s. (2.5) n.s. (2.7)
(4.5)* n.s. (1.2) n.s. (0.2)
n.s. (0.6) n.s. (0.1) n.s. (0.2)
Values are means of five replicates (s.d.). DNA yield was measured as PicoGreen absorbance and related to root dry weight (RDW). Copy numbers (CN) of Rhizophagus sp. per nanogram of isolated DNA are presented both uncorrected and corrected by the recovery of internal DNA standard (IS). Significant effects are given according to ANOVA (with F value in parentheses. Means marked with the same letter are not significantly different at P≤ 0.05 according to Tukey’s multiple comparison test n.s. non-significant effect (P>0.05) * P ≤ 0.05; ***P≤0.001
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fungal colonization is usually not recorded (our approach completely flattens the difference between 1 and 100 hyphae crossing a single intersection, for instance). The absence of positive correlation between AMF mtDNA copy numbers and microscopically determined fungal abundance does therefore not per se disqualify the molecular quantification data, but obviously, more work using independent approaches such as high-resolution 3D morphometry or lipid analyses are required to solve this conundrum. The microscopically determined fungal abundance data do therefore not help to decide which of the molecular data sets more correctly approximates the reality. However, a decline of AMF DNA in roots, as described in our study has been reported independently from different laboratories, using different qPCR assays, materials, fungal strains, and calculations (Janoušková et al. 2013; Jansa et al. 2008; Thonar 2009). Sometimes, this decline was accompanied by a negative correlation of the molecular data with microscopically determined abundance of fungal structures in roots (Thonar 2009) similarly as in this study. It has been explained by decreasing vitality of fungal structures with increasing age, and this assumption is consistent with an early peak of phosphorus uptake benefits in mycorrhizal plants (Thonar 2009) and a peak in intraradical hyphal vitality, which has been independently demonstrated using vital staining of AMF structures (Tisserant et al. 1993; Vierheilig et al. 2005). However, if the amount of the fungal DNA in the roots really declines with root age, how could the data from dry roots, indicating up to sixfold higher fungal DNA levels than the data from frozen roots in the last harvest, be explained? Could DNA fragmentation cause much higher PCR efficiency required to explain this phenomenon, or does the grinding of dry roots release DNA from fungal structures, which are not properly disintegrated, and thus DNA is not released from them when frozen roots are used? Such structures could be intraradical spores, which contain high amounts of nuclei and are abundantly produced by Rhizophagus sp. Intraradical spores and/or vesicles were also present in the material collected for this study (Table 6). Their frequency did not differ among the harvests, but their resistance to mechanical disintegration may have changed during the spore maturation process, i.e., by thickening of their walls. Another important methodological issue to consider in this context is the different levels of protection against the growth of saprotrophic fungi provided by the two material preservation approaches and the possibility that dry material becomes contaminated by saprotrophic fungi during the storage. Though amplification of non-target fungal phyla can be excluded when using TaqMan systems designed and optimized to discriminate closely related AMF species as the system employed here (see Kiers et al. 2011), such a non-target amplification sometimes occurs by primers designed to amplify a DNA fragment of all
AMF or major phylogenetic groups (Douhan et al. 2005; Kohout et al. 2014). Consequently, while non-target amplification from dry root material can be excluded to have biased the results of this study, it must be considered in studies aiming at quantification of AMF by more general primers. Which other factors may then be responsible for the absence of correlation between AMF copy numbers in frozen and dry root materials? The discrepancy between the two molecular data sets was not just related to root age as could be suggested by the significant interaction of the factors material and plant age and highly divergent fungal DNA levels in the frozen and dry materials from the last harvest. The correlation of the data sets was not improved when data from the last harvest were excluded from the analysis. Heterogeneity of AMF structures in roots (Gamper et al. 2008) can also be excluded as the main responsible factor because the values from extracts processed by the two extraction methods were well correlated within each type of material. A possible clue is provided by the higher variability among root systems in the data from dry material as compared to the frozen material. It indicates that the efficiency of DNA extraction and/or amplification of AMF DNA randomly varied among root systems due to drying and/or subsequent storage. We may hypothesize high susceptibility of AMF DNA to minute differences in the conditions of the drying process, which is influenced not only by temperature but also by the amount and density of the drying material. In contrast to the variability among root systems, variability in AMF copy numbers within root systems did not differ between frozen and dry materials. This corroborates the conclusion that the variability in data from dry material was indeed root system related, not sample related. On the other hand, we have to reject our hypothesis that the use of dry roots could facilitate representative sampling of root material. Our data also indicate that spatial heterogeneity of root colonization by AMF is not the main reason for high variability in AMF copy numbers among replicates in contrast to the previous results of Gamper et al. (2008). In conclusion, we show that AMF DNA can be effectively extracted and amplified from dry root material in similar or even higher amounts than from frozen material provided PCR inhibition is prevented. On the other hand, our results indicate higher variability introduced to the results by using dry roots as compared to frozen roots and poor comparability of the results obtained by both approaches. The latter finding points to the vital importance of sample preservation and preparation approaches for the collection of quantitative data and strongly encourages their further investigation. This must be especially considered at developing standard methods for fungal DNA quantification in environmental samples. This should include also standardized material handling prior to the PCR steps to reduce experimental noise.
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While our results discouraged from using dry material for precise and highly reproducible quantification of AMF DNA in roots, they also show that DNA extracts from dry root material may be well suitable for non-quantitative screening of the presence of specific AMF by qPCR provided DNA extraction is tuned up so as to minimize the effect of PCR inhibitors. DNA extracts from dry roots have been previously successfully utilized for the detection of specific AMF taxa by nested PCR (Farmer et al. 2007) or for the amplification of AMF DNA with general primers (e.g., Alguacil et al. 2008; Cesaro et al. 2008). In comparison with those approaches, however, qPCR has distinctly lower requirements on manipulation and time (Filion et al. 2003; König et al. 2010). As it is also more sensitive than conventional PCR (Li et al. 2008; Minerdi et al. 2008), it holds promise to become the method of choice for fast screening of specific fungal taxa also in material conserved by drying, when the associated method limitations are carefully considered. Acknowledgments This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic, project no. LK11224, and by the long-term research development programs RVO 67985939 and RVO 61388971 in frame of the Joint Working Group of the Institute of Microbiology AS CR and the Institute of Botany AS CR. We are grateful to Hana Hršelová, Petra Bukovská, and Milan Gryndler for the technical advice, to Hana Gryndlerová for the technical assistance, and to two anonymous reviewers for their constructive comments.
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symbiosis. New Phytol 133:123–134. doi:10.1111/j.1469-8137. 1996.tb04348.x Sanzani SM, Nicosia M, Faedda R, Cacciola SO, Schena L (2014) Use of quantitative PCR detection methods to study biocontrol agents and phytopathogenic fungi and oomycetes in environmental samples. J Phytopathol 162:1–13. doi:10.1111/jph.12147 Schena L, Nicosia M, Sanzani SM, Faedda R, Ippolito A, Cacciola SO (2013) Development of quantitative PCR detection methods for phytopathogenic fungi and oomycetes. J Plant Pathol 95:7–24. doi:10.4454/JPP.V95I1.016 Smith SE, Read DJ (2008) Mycorrhizal symbiosis, 3rd edn. Academic, Amsterdam Thonar C (2009) Synthetic mycorrhizal communities—establishment and functioning. Dissertation, ETH Zürich Thonar C, Erb A, Jansa J (2012) Real-time PCR to quantify composition of arbuscular mycorrhizal fungal communities—marker design, verification, calibration and field validation. Mol Ecol Resour 12(2):219–232. doi:10.1111/j.1755-0998.2011.03086.x Thonar C, Frossard E, Šmilauer P, Jansa J (2014) Competition and facilitation in synthetic communities of arbuscular mycorrhizal fungi. Mol Ecol 23:733–746. doi:10.1111/mec.12625 Tisserant B, Gianinazzi-Pearson V, Gianinazzi S, Gollotte A (1993) In planta histochemical staining of fungal alkaline phosphatase activity for analysis of efficient arbuscular mycorrhizal infections. Mycol Res 97:245–250. doi:10.1016/S0953-7562(09)80248-7 van der Heijden MGA, Klironomos JN, Ursic M, Moutoglis P, StreitwolfEngel R, Boller T, Wiemken A, Sanders IR (1998) Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature 396:69–72 Vierheilig H, Schweiger P, Brundrett M (2005) An overview of methods for the detection and observation of arbuscular mycorrhizal fungi in roots. Physiol Plant 125:393–404. doi:10.1111/j.1399-3054.2005. 00564.x Wagg C, Jansa J, Stadler M, Schmid B, van der Heijden MGA (2011) Mycorrhizal fungal identity and diversity relaxes plant-plant competition. Ecology 92:1303–1313. doi:10.1890/10-1915.1
ORIGINAL PAPER
Quantification of arbuscular mycorrhizal fungal DNA in roots: how important is material preservation? Martina Janoušková & David Püschel & Martina Hujslová & Renata Slavíková & Jan Jansa
Received: 30 May 2014 / Accepted: 21 August 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract Monitoring populations of arbuscular mycorrhizal fungi (AMF) in roots is a pre-requisite for improving our understanding of AMF ecology and functioning of the symbiosis in natural conditions. Among other approaches, quantification of fungal DNA in plant tissues by quantitative realtime PCR is one of the advanced techniques with a great potential to process large numbers of samples and to deliver truly quantitative information. Its application potential would greatly increase if the samples could be preserved by drying, but little is currently known about the feasibility and reliability of fungal DNA quantification from dry plant material. We addressed this question by comparing quantification results based on dry root material to those obtained from deep-frozen roots of Medicago truncatula colonized with Rhizophagus sp. The fungal DNA was well conserved in the dry root samples with overall fungal DNA levels in the extracts comparable with those determined in extracts of frozen roots. There was, however, no correlation between the quantitative data sets obtained from the two types of material, and data from dry roots were more variable. Based on these results, we recommend dry material for qualitative screenings but advocate using frozen root materials if precise quantification of fungal DNA is required.
Electronic supplementary material The online version of this article (doi:10.1007/s00572-014-0602-7) contains supplementary material, which is available to authorized users. M. Janoušková : D. Püschel : M. Hujslová : R. Slavíková : J. Jansa Institute of Microbiology, Academy of Sciences of the Czech Republic, Vídeňská 1083, 142 20 Praha 4 – Krč, Czech Republic M. Janoušková (*) : D. Püschel Institute of Botany, Academy of Sciences of the Czech Republic, Zámek 1, 252 43 Průhonice, Czech Republic e-mail: [email protected]
Keywords Arbuscular mycorrhizal fungi . Intraradical colonization . PCR inhibition . Quantitative real-time PCR (qPCR) . Sample preservation
Introduction Many fungal groups colonize living plant tissues and form mutualistic, parasitic, or neutral relationships with plants. Monitoring their populations is vital for plant protection in the case of pathogenic fungi and important for improving our understanding of basic ecological questions in the case of other fungal groups. Communities of obligatory biotrophic arbuscular mycorrhizal fungi (AMF), for example, importantly influence the productivity and diversity of plant communities as well as nutrient and energy fluxes between plants and the soil system (van der Heijden et al. 1998; Smith and Read 2008). The intraradical structures of AMF do not enable reliable microscopic discrimination of species while communities of soil-borne spores with diagnostic morphological features do not reflect the diversity of AMF symbionts actually interacting with plants. Rising interest in AMF communities goes therefore hand in hand with development of DNA-based tools, which have become indispensable in AMF research. DNAbased techniques enabled discovering new aspects of AM symbiosis such as high hidden diversity of AMF (Clapp et al. 1995; Öpik et al. 2009; Sanders et al. 1996) or specific interactions between certain plant and AMF taxa (Davison et al. 2011; Gollotte et al. 2004; Helgason et al. 2002). With current scientific questions going deeper into AMF community ecology, high throughput techniques are required to process large numbers of samples. Here, quantitative realtime PCR (qPCR) with taxon-specific primers and/or probes is gaining increasing attention (Alkan et al. 2006; Janoušková et al. 2013; Jansa et al. 2008; Jansa et al. 2014; Thonar et al.
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2012; Thonar et al. 2014; Wagg et al. 2011). It is currently the only approach enabling, at the same time, discrimination and precise quantification of specific sequence motifs in roots colonized by multiple AMF taxa. In comparison with merely qualitative tools such as construction of sequence libraries, terminal restriction fragment length polymorphism, or other fingerprinting methods, its main advantage is in recording subtle shifts in relative abundances of the individual taxa besides their presence/absence (Thonar et al. 2014). The application of qPCR in community research of mycorrhizal and other endophytic fungi is however still in its beginning as evident from comparison with the field of fungal phytopathology, where qPCR, after two decades of basic research, is becoming a routine tool of early pathogen detection (Sanzani et al. 2014). Analogically, qPCR could become an alternative technique to subjectivity-prone microscopy for determining the overall abundance of non-pathogenic fungi in plant tissues, profiting from its high throughput and reproducibility. DNA-based methods impose certain requirements on sample preservation, which have to be balanced with other requirements or limitations of a study setup. Specifically, deepfreezing is without doubt the best choice for the preservation of biomolecules including DNA, but drying or chemical conservation is more convenient and often the only possible approach when sampling takes place far away from appropriately equipped laboratories. Both alternative approaches have been successfully applied to material used for AMF community analyses by sequencing of amplified fragments of ribosomal DNA, e.g., by Alguacil et al. (2008), Cesaro et al. (2008), and Öpik et al. (2003). On the other hand, poor amplification of AMF DNA from dry root material has been reported, and more rapid degradation of AMF DNA due to the drying process has been suggested, as compared to plant DNA (Bainard et al. 2010). Quantitative data are more sensitive to bias by low quality of DNA extracts such as presence of inhibitors or DNA fragmentation (Bustin 2004). For this reason, studies utilizing qPCR for fungal detection predominantly rely on fresh material or on cryogenic sample preservation. However, if drying proved sufficient as a sample conservation approach, it would greatly broaden the application potential of fungal quantification by qPCR. For instance, it would enable evaluation of samples from remote areas, which are highly underrepresented in microbial diversity studies as demonstrated for AMF by Öpik et al. (2010). Furthermore, the use of dry material could have important advantages in processing of experimental samples as it would facilitate representative sampling. High spatial heterogeneity of AMF nuclei in their intraradical structures is difficult to account for by sampling fresh segments from the entire root system (Gamper et al. 2008). Homogenization of larger amounts of roots, easy to achieve by milling of dry samples, could greatly increase the representativeness of sampling.
There is however no information on whether dry material can render reliable qPCR data on AMF abundance in plant tissues. We therefore focused on the feasibility and reliability of quantification of AMF DNA from dry root powder as alternative to frozen root material. We compared root material of different ages to account for dynamics of the fungal DNA levels in roots (Jansa et al. 2008; Krak et al. 2012; Thonar 2009) and potential effects of plant age on the quality of DNA extracts. We designed our experiments to answer the following main questions: (1) Does qPCR on DNA extracts from dry roots produce the same results as on DNA extracts from frozen samples? (2) Can the use of dry root powder, in comparison to frozen roots, decrease the variability of qPCR measurements?
Material and methods Material preparation Seeds of Medicago truncatula Gaertn. J5 were soaked for 7 min in 96 % H2SO4, and pre-germinated for 2 days on a moist filter paper. Cultivation substrate was prepared by mixing autoclaved sand (45 %), autoclaved zeolite (45 %), and γ-sterilized silty-clay soil (10 %), which had the following main characteristics: pH (water)=8.9, total P 46 mg kg−1, water-extractable P 2.6 mg kg−1, total N 0.13 g kg−1, and organic C 2.2 g kg−1. Fifteen pots (volume 2 L, height 21 cm) were filled with the cultivation substrate, which was amended with 5 % (v:v) of inoculum of the arbuscular mycorrhizal fungus Rhizophagus sp. “Chomutov” (formerly Glomus intraradices “Chomutov”); for origin and cultivation history of this isolate, see Krak et al. (2012). The inoculum was prepared by air-drying and homogenization of the substrate of a one-year-old culture of this AMF isolate on maize and Desmodium sp. and contained chopped roots, extraradical mycelium and spores in the original cultivation substrate. Two pre-germinated seeds were planted into each pot, and non-vital seedlings were replaced after 1 week. The seedlings were inoculated at planting with 1 ml of suspension of Sinorhizobium meliloti isolate number 1021 from INRA Toulouse. The bacterial inoculum was prepared by cultivation in tryptone-yeast extract broth for 2 days and subsequent washing with 0.5 % MgSO4. The plants were cultivated in a greenhouse (14 h photoperiod) with supplemental metal halide discharge lamps (min. 8 klux) and fertilized once per week with 100 ml of P2N3 solution (Gryndler et al. 1992) with P concentration in the nutrient solution reduced to 20 μM. The pots were harvested after 57 (harvest 1), 68 (harvest 2), and 90 (harvest 3) days of cultivation, five pots per harvest. The root systems of the plants were carefully lifted from the pots, washed, dried in paper tissue, and stretched out. The
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upper 5 cm of the root systems were removed, and the roots from the depths of approximately 5–15 cm were used for sampling. The roots were cut to fragments of about 2 cm in length. Five samples of 100 mg fresh weight were collected by randomly picking root segments, immediately frozen in liquid nitrogen, and stored at −80 °C for molecular quantification of fungal DNA. A sample of about 500 mg root fresh weight was collected in the same way for microscopic determination of root colonization and stored in 50 % ethanol. The rest of this part of the root system was dried at 60 °C, pulverized in a ball mill (Retsch MM 200, Haan, Germany; 25 Hz, 2 min), and stored dry at room temperature for 3–4 months before DNA extraction. The extent of root length colonized by fungal structures was determined after trypan blue staining (Koske and Gemma 1989) using the magnified intersection method (McGonigle et al. 1990). Fifty root intersects were scored per sample. No attempt was made to distinguish intraradical spores from vesicles as this cannot be done with certainty on trypan bluestained roots. DNA extraction and characterization of the extracts DNA was extracted from the deep-frozen and dried root samples using two DNA extraction approaches resulting in a total of four combinations of material × DNA extraction method (extraction treatments). DNeasy Plant Mini Kit (QIAGEN, Hilden, Germany) was chosen as one DNA extraction approach and performed according to the manufacturer’s instructions, the glassmilk method described by Gryndler et al. (2013) as the other. Briefly, after incubation of homogenized plant material in CTAB extraction buffer, the extracts were purified by chloroform and combined with the bind buffer (saturated NaCl with 10 mM Bis-Tris, pH 6.0) and 50 % glassmilk (water suspension of acid-washed silicon dioxide). After centrifugation, washing, and drying of the pellet, it was resuspended and centrifuged again to transfer the extracted DNA into solution and separate it from the silicon dioxide particles. Aliquots of 100 mg of frozen roots were thoroughly homogenized using liquid nitrogen and a mortar and pestle for both DNA extraction methods. The dry root powder was weighted to 20 mg or 10 mg for the kit or the glassmilk extraction method, respectively, and thoroughly vortexed with the appropriate lysis buffer. The kit-extracted DNA was eluted with 80 μl of 10 mM Tris-HCl buffer (pH 7.5); the glassmilkextracted DNA was resuspended in 50 μl of 10 mM TrisEDTA (TE) buffer (pH 7.5). All DNA extracts were stored at −80 °C until use. Experimental treatments and numbers of extractions processed per root system are summarized in Table 1. DNA concentration in the extracts was determined spectrophotometrically using NanoDrop 1000 Spectrophotometer
(Thermo Scientific, Waltham, USA) and fluorometrically using Quant-iT PicoGreen® dsDNA Assay Kit (Invitrogen, Carlsbad, USA) and Infinite M200 microplate reader (Tecan, Männedorf, Switzerland). As correlation between these two measurements was poor and spectrophotometry substantially overestimated DNA concentrations in nearly all treatments (except in the kit extracts from frozen material), the values determined by PicoGreen fluorescence were used in all subsequent calculations. The DNA yield of the extractions (amount of extracted DNA per sample) was calculated to ng DNA mg−1 of root dry weight. The average coefficient of dry to fresh root weight obtained from all harvested root systems was used for the calculation of root dry weight of the frozen samples. The integrity of the extracted DNA was visually assessed after electrophoresis of the DNA extracts in 1 % agarose gel with ethidium bromide. qPCR experiments The following experiments were conducted: (1) Evaluation of the effect of material and DNA extraction method on PCR inhibition by the DNA extracts. This was determined using one extract per root system and extraction treatment, i.e., on 60 extracts in total. All DNA extracts were measured at tenfold dilution; extracts from harvests 1 and 3 also at two- and fivefold dilutions. (2) Evaluation of the effect of material and DNA extraction method on AMF mitochondrial ribosomal DNA (mtDNA) copy numbers in the DNA extracts. This evaluation was based on the same set of extracts as the experiment 1; all extracts were measured at tenfold dilution only. (3) Comparison of the variability of PCR inhibition by the DNA extracts within root system between DNA extracts from frozen and dry root materials. This was determined on 3 kit extracts were used for the determination extracts per root system and material including only samples from harvests 1 and 3, i.e., on 60 extracts in total. The extracts were measured at tenfold dilution only. (4) Comparison of the variability of AMF mtDNA copy numbers within root system between DNA extracts from frozen and dry root samples. This evaluation was based on the same set of extracts as the experiment 3 (at tenfold dilution). The qPCRs were performed in StepOnePlus instrument (Applied Biosystems, Foster City, USA). The PCR mix (total volume 20 μl) contained 1x HOT FIREPol® Probe qPCR Mix Plus with ROX reference dye (Solis BioDyne, Tartu, Estonia), 0.5 μM each primer, 0.125 μM probe, and 2 μl of template. Each sample was ran in technical duplicates or triplicates, which were averaged for all further calculations. Inhibition of qPCR by the DNA extracts was tested by determining the recovery of known amounts of internal DNA standard (IS) in the presence of the DNA extracts. The IS— linearized plasmid carrying a fragment of cassava mosaic virus (GenBank accession AJ4279140)—was added into PCR reactions in the amount of 2×106 copy numbers per
Mycorrhiza Table 1 Numbers of samples extracted per root system from dry or frozen materials using either QIAGEN DNeasy Plant Mini Kit (kit) or the glassmilk method (Gryndler et al. 2013). Five replicate root systems were extracted per harvest
Material
Extraction method
Frozen
Kit Glassmilk Kit Glassmilk
Dry Total
Total×5 root systems
reaction in 10 mM TE buffer (pH 7.5). The IS was then quantified using the assay of Thonar et al. (2012): forward primer 5′-CGAACCTGGACTGTTATGATG-3′, reverse primer 5′-AATAAACAATCCCCTGTATTTCAC-3′, TaqMan probe FAM-CACCAGGCACCAACAACGACCATTBHQ1. The DNA extracts were added in the amount of 2 μl, diluted as specified above. The reaction conditions were as follows: initial denaturation for 15 min at 95 °C followed by 45 cycles of denaturation (95 °C, 10 s), annealing (50 °C, 20 s), and extension (72 °C, 10 s). Mitochondrial large ribosomal subunit gene (mtDNA) of Rhizophagus sp. was quantified as described previously by Kiers et al. (2011, assay for G. intraradices) using the following primers: forward primer 5′-TTTTAGCGATAGCGTAAC AGC-3′, reverse primer 5′-TACATCTAGGACAGGGTTTC G-3′, and TaqMan probe FAM-AAACTGCCACTCCCTC CATATCCAA-BHQ1. The reaction conditions were initial denaturation for 15 min at 95 °C followed by 45 cycles of denaturation (95 °C, 10 s), annealing (54 °C, 1 min), and extension (72 °C, 10 s). Threshold cycle (Ct) values were converted to copy numbers (CN) μl−1 of template using standard curves previously established under the same cycling conditions as described above. The standard curve for the IS assay was based on fivefold dilutions of the linearized plasmid spanning the concentration from 109 to 20 copies μl−1 template. It was constructed by plotting the Ct values against logarithmically transformed concentrations. The equation of the standard curve was y=−3.595x+43.327 (R2 =0.9997) where x = log copies μl−1 template and y=Ct. Recovery of the IS was calculated as R(%)=CNsample/CNblank ×100, where CNsample stands for the copy numbers of IS determined in the corresponding sample, and CNblank for the copy numbers determined in control samples ran on the same plate with ddH2O added to the reaction mix instead of DNA extract. The standard curve for the Rhizophagus sp. assay was constructed with a fourfold serial dilution series of linearized plasmid containing the respective amplicon (1011−1.3 104 CN μl−1). The resulting equation was y=−3.700x+48.837 (R2 = 0.9952). The copy numbers per μl template were converted to CN ng−1 extracted DNA using the sample-specific DNA concentrations determined by PicoGreen fluorescence. These values were corrected by sample-specific IS recovery for the
Harvest 1 (57 days)
Harvest 2 (68 days)
Harvest 3 (90 days)
3 1 3 1 8
1 1 1 1 4
3 1 3 1 8
40
20
40
respective template dilution to account for differences in PCR inhibition among samples, i.e., they were calculated to values, which would have been obtained without any inhibition. Data analysis Relationships between the different data sets were tested by correlation analysis. Effects of the factors material (dry vs. frozen), extraction method (kit vs. glassmilk) and plant age on DNA yield, IS recovery, and AMF mtDNA copy numbers were assessed by three-way ANOVA or by non-parametric Kruskal-Wallis test when the data did not meet the assumptions of ANOVA. Root colonization data were evaluated by one-way ANOVA. Multiple comparisons were conducted with Tukey’s multiple comparison test. Variability among samples from one root system was expressed as a coefficient of variation (CV), which was calculated from the qPCR results of the three extracts analyzed per each root system and type of material. Effects of the factors’ material and plant age on CV were assessed by twoway ANOVA. The CV was also used to compare variability in AMF mtDNA copy numbers among root systems based on data from experiment 2. CV was calculated for each combination of extraction treatment and harvest based on values obtained for the five replicate root systems. Effects of the factors’ material and extraction procedure were assessed by two-way ANOVA regarding the three harvests as replicates within extraction treatment. All statistical analyses were carried out in Statistica 12 (StatSoft, Tulsa, USA).
Results Characteristics of the DNA extracts DNA yields of the extracts did not differ between the two materials; they were generally higher in kit extracts than in glassmilk extracts and increased with plant age (Table 2). DNA integrity visually assessed after electrophoresis in agarose gels was highest in kit extracts from frozen roots, where a
Mycorrhiza Table 2 Yields of DNA extractions from dry or frozen root materials obtained either with QIAGEN DNeasy Plant Mini Kit (kit) or using the glassmilk method (Gryndler et al. 2013) and the effect of tenfold-diluted DNA extracts on the recovery of internal DNA standard (IS) Material
Dry
Extraction method
Plant age (days)
Yield (ng DNA mg−1 RDW)
Recovery of IS (%)
Dry
Frozen
Dry
Frozen
Kit
57
174a (42)a
100a (35)y
78 (8)bc
94 (9)a
Glassmilk
68 90 57 68 90
151 (29)a 204a (17)a 94 (27)b 88 (18)b 146 (4)a Significant effects n.s. (1.2) (6.9)** (14.5)*** n.d. n.d. n.d. n.d.
215 (75)x 225a (42)x 160 (59)xy 227 (40)x 151 (21)xy
68 (8)c 61 (15)c 102 (3)a 93 (7)ab 94 (4)a
89 (7)ab 90 (6)ab 97 (2)a 97 (1)a 95 (3)a
Material (A) Extraction method (B) Plant age (C) A×B A×C B×C A×B×C
(26.1)*** (69.6)*** (6.0)** (27.6)*** n.s. (1.1) n.s. (0.2) n.s. (0.5)
Values are means of five or 15 replicates (the latter marked with a ) with s.d. in parentheses. DNA yield is based on PicoGreen fluorescence and related to root dry weight (RDW). Significant effects are given according to ANOVA (with F values in parentheses) for the parameter recovery of IS or according to Kruskal-Wallis non-parametric test (H values in parentheses) for the parameter yield. Means with the same letters are not significantly different at the threshold P≤0.05 according to Tukey’s multiple comparison test. For DNA yield, the Tukey test was conducted for each material separately in order to meet the assumption on homogeneity of variance n.s. non-significant effect (P>0.05), n.d. not determined **P≤0.01; ***P≤0.001
distinct band was apparent. In the other extracts, DNA was clearly more degraded (Online Resource, Fig. S1). DNA integrity was not visibly affected by plant age. Recovery of the IS, as an inverse measure of PCR inhibition by DNA extracts, was distinctly more affected by the presence of kit extracts from dry material as compared to the other three extraction treatments: hardly any IS could be amplified, testifying nearly total PCR inhibition, when the kit extracts from dry material were diluted only twofold, while IS recovery was at least 72 % in the presence of the other extracts at this dilution (Fig. 1). At tenfold dilution, kit extracts from dry material still caused significantly higher PCR inhibition than the other extracts. In addition, the inhibitory effect of the DNA extracts slightly but significantly increased with plant age (Table 2).
According to three-way ANOVA, AMF mtDNA copy numbers were significantly affected by material (F=6.7, P= 0.013), plant age (F=10.9, P0.05) *P≤0.05
extraction approach and added undiluted DNA extracts into their qPCRs without specifically considering PCR inhibition. This comparison highlights the need of using internal controls to exclude the negative impact of PCR inhibitors on the accuracy of qPCR detection of microorganisms in environmental samples (Schena et al. 2013). The pattern of amplification of AMF DNA from dry roots provides some support for using this approach of conserving root samples, but the discrepancy between results from frozen and dry root materials questions the reliability of the obtained data. The dynamics of AMF development found in frozen roots was characterized by a decline of AMF copy numbers in the last harvest, whereas fungal DNA as detected in extracts from dry roots remained high throughout. Neither the data
from frozen roots nor those from dry roots were however positively correlated with any of the parameters of root colonization determined microscopically (correlation was either absent or even negative). Comparability of qPCR data to microscopically determined root colonization by AMF was the main topic of the first studies focused on the qPCR as an approach to quantify development of AMF in roots and/or soil (Alkan et al. 2004; Gamper et al. 2008; Isayenkov et al. 2004). Later, it has become evident that DNA levels must be regarded as another measure of the fungal abundance, especially when root colonization of different age is evaluated, as qPCR data reflect not only the biomass but probably also the vitality of the fungal structures (Gamper et al. 2008; Jansa et al. 2008; Kiers et al. 2011; Krak et al. 2012). Furthermore, the microscopy approach employed here and in most other studies does provide only a crude approximate of fungal biomass as the intensity of
Table 5 Variability among triplicate samples from one root system expressed as coefficient of variation Material
Plant age (days)
ng DNA mg−1 RDW
Recovery of IS (%)
CN ng−1 uncorrected
CN ng−1 corrected
Dry
57 90 57 90
0.09 (0.03)b 0.08 (0.02)b 0.29 (0.10)a 0.24 (0.10)a Significant effects (31.3)***
0.07 (0.05) 0.17 (0.10) 0.07 (0.04) 0.07 (0.03)
0.15 (0.12) 0.09 (0.05) 0.22 (0.08) 0.20 (0.09)
0.17 (0.11) 0.17 (0.09) 0.19 (0.06) 0.23 (0.11)
Frozen
Material (A) Age (B) AxB
n.s. (0.6) n.s. (0.2)
n.s. (2.4) n.s. (2.5) n.s. (2.7)
(4.5)* n.s. (1.2) n.s. (0.2)
n.s. (0.6) n.s. (0.1) n.s. (0.2)
Values are means of five replicates (s.d.). DNA yield was measured as PicoGreen absorbance and related to root dry weight (RDW). Copy numbers (CN) of Rhizophagus sp. per nanogram of isolated DNA are presented both uncorrected and corrected by the recovery of internal DNA standard (IS). Significant effects are given according to ANOVA (with F value in parentheses. Means marked with the same letter are not significantly different at P≤ 0.05 according to Tukey’s multiple comparison test n.s. non-significant effect (P>0.05) * P ≤ 0.05; ***P≤0.001
Mycorrhiza
fungal colonization is usually not recorded (our approach completely flattens the difference between 1 and 100 hyphae crossing a single intersection, for instance). The absence of positive correlation between AMF mtDNA copy numbers and microscopically determined fungal abundance does therefore not per se disqualify the molecular quantification data, but obviously, more work using independent approaches such as high-resolution 3D morphometry or lipid analyses are required to solve this conundrum. The microscopically determined fungal abundance data do therefore not help to decide which of the molecular data sets more correctly approximates the reality. However, a decline of AMF DNA in roots, as described in our study has been reported independently from different laboratories, using different qPCR assays, materials, fungal strains, and calculations (Janoušková et al. 2013; Jansa et al. 2008; Thonar 2009). Sometimes, this decline was accompanied by a negative correlation of the molecular data with microscopically determined abundance of fungal structures in roots (Thonar 2009) similarly as in this study. It has been explained by decreasing vitality of fungal structures with increasing age, and this assumption is consistent with an early peak of phosphorus uptake benefits in mycorrhizal plants (Thonar 2009) and a peak in intraradical hyphal vitality, which has been independently demonstrated using vital staining of AMF structures (Tisserant et al. 1993; Vierheilig et al. 2005). However, if the amount of the fungal DNA in the roots really declines with root age, how could the data from dry roots, indicating up to sixfold higher fungal DNA levels than the data from frozen roots in the last harvest, be explained? Could DNA fragmentation cause much higher PCR efficiency required to explain this phenomenon, or does the grinding of dry roots release DNA from fungal structures, which are not properly disintegrated, and thus DNA is not released from them when frozen roots are used? Such structures could be intraradical spores, which contain high amounts of nuclei and are abundantly produced by Rhizophagus sp. Intraradical spores and/or vesicles were also present in the material collected for this study (Table 6). Their frequency did not differ among the harvests, but their resistance to mechanical disintegration may have changed during the spore maturation process, i.e., by thickening of their walls. Another important methodological issue to consider in this context is the different levels of protection against the growth of saprotrophic fungi provided by the two material preservation approaches and the possibility that dry material becomes contaminated by saprotrophic fungi during the storage. Though amplification of non-target fungal phyla can be excluded when using TaqMan systems designed and optimized to discriminate closely related AMF species as the system employed here (see Kiers et al. 2011), such a non-target amplification sometimes occurs by primers designed to amplify a DNA fragment of all
AMF or major phylogenetic groups (Douhan et al. 2005; Kohout et al. 2014). Consequently, while non-target amplification from dry root material can be excluded to have biased the results of this study, it must be considered in studies aiming at quantification of AMF by more general primers. Which other factors may then be responsible for the absence of correlation between AMF copy numbers in frozen and dry root materials? The discrepancy between the two molecular data sets was not just related to root age as could be suggested by the significant interaction of the factors material and plant age and highly divergent fungal DNA levels in the frozen and dry materials from the last harvest. The correlation of the data sets was not improved when data from the last harvest were excluded from the analysis. Heterogeneity of AMF structures in roots (Gamper et al. 2008) can also be excluded as the main responsible factor because the values from extracts processed by the two extraction methods were well correlated within each type of material. A possible clue is provided by the higher variability among root systems in the data from dry material as compared to the frozen material. It indicates that the efficiency of DNA extraction and/or amplification of AMF DNA randomly varied among root systems due to drying and/or subsequent storage. We may hypothesize high susceptibility of AMF DNA to minute differences in the conditions of the drying process, which is influenced not only by temperature but also by the amount and density of the drying material. In contrast to the variability among root systems, variability in AMF copy numbers within root systems did not differ between frozen and dry materials. This corroborates the conclusion that the variability in data from dry material was indeed root system related, not sample related. On the other hand, we have to reject our hypothesis that the use of dry roots could facilitate representative sampling of root material. Our data also indicate that spatial heterogeneity of root colonization by AMF is not the main reason for high variability in AMF copy numbers among replicates in contrast to the previous results of Gamper et al. (2008). In conclusion, we show that AMF DNA can be effectively extracted and amplified from dry root material in similar or even higher amounts than from frozen material provided PCR inhibition is prevented. On the other hand, our results indicate higher variability introduced to the results by using dry roots as compared to frozen roots and poor comparability of the results obtained by both approaches. The latter finding points to the vital importance of sample preservation and preparation approaches for the collection of quantitative data and strongly encourages their further investigation. This must be especially considered at developing standard methods for fungal DNA quantification in environmental samples. This should include also standardized material handling prior to the PCR steps to reduce experimental noise.
Mycorrhiza
While our results discouraged from using dry material for precise and highly reproducible quantification of AMF DNA in roots, they also show that DNA extracts from dry root material may be well suitable for non-quantitative screening of the presence of specific AMF by qPCR provided DNA extraction is tuned up so as to minimize the effect of PCR inhibitors. DNA extracts from dry roots have been previously successfully utilized for the detection of specific AMF taxa by nested PCR (Farmer et al. 2007) or for the amplification of AMF DNA with general primers (e.g., Alguacil et al. 2008; Cesaro et al. 2008). In comparison with those approaches, however, qPCR has distinctly lower requirements on manipulation and time (Filion et al. 2003; König et al. 2010). As it is also more sensitive than conventional PCR (Li et al. 2008; Minerdi et al. 2008), it holds promise to become the method of choice for fast screening of specific fungal taxa also in material conserved by drying, when the associated method limitations are carefully considered. Acknowledgments This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic, project no. LK11224, and by the long-term research development programs RVO 67985939 and RVO 61388971 in frame of the Joint Working Group of the Institute of Microbiology AS CR and the Institute of Botany AS CR. We are grateful to Hana Hršelová, Petra Bukovská, and Milan Gryndler for the technical advice, to Hana Gryndlerová for the technical assistance, and to two anonymous reviewers for their constructive comments.
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