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DOI: 10.3852/mycologia.98.3.384
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Mycologia, 98(3), 2006, pp. 384-392.
© 2006 by The Mycological Society of America

Comparison of taxonomic, colony morphotype and PCR-RFLP methods to characterize microfungal diversity


Lidia S. Watrud 1

     U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Western Ecology Division, 200 SW 35th Street, Corvallis, Oregon 97333

Kendall Martin
Kelly K. Donegan

     Dynamac Corp., 200 SW 35th Street, Corvallis, Oregon 97333

Jeffrey K. Stone

     Oregon State University, Department of Botany and Plant Pathology, Corvallis, Oregon 97331

Clarace G. Coleman

     National Asian Pacific Center on Aging, 1511 Third Avenue, Seattle, Washington 98101

    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 

We compared three methods for estimating fungal species diversity in soil samples. A rapid screening method based on gross colony morphological features and color reference standards was compared with traditional fungal taxonomic methods and PCR-RFLP for estimation of ecological indices of soil microfungal community composition. Normalized counts of colony morphotypes on dichloran rose bengal medium were used to estimate species richness (S) and evenness ( J) and to calculate Shannon’s diversity (H) and Simpson’s (SI) dominance indices. Isolates were obtained by dilution plating techniques from litter and soil layer samples taken from Douglas-fir forest and clear-cut areas at two locations in the Cascade Mountains. The highest correspondence (97%) was observed between taxonomic identification and RFLP patterns (32:33). Cladistic analyses of PCR-RFLP patterns indicated an 81% correspondence between RFLP patterns:colony morphotypes (33:41). A correspondence of 78% was observed between traditional taxonomic identification:colony morphotypes (32:41). Statistical analyses of ecological indices based on quantitative application of the colony morphotyping method indicated significant differences (P < 0.05) in fungal community composition between forested and clear-cut areas at the Toad Road site but not at the Falls Creek site. Comparisons of ecological indices based on traditional identification of taxa by microscopic characterization on defined culture media resulted in identical findings of statistical significance. The colony morphotyping approach is proposed as a screening method to identify potential effects of land management practices, edaphic factors and pollutants on microfungal diversity.

Key words: ecological indices, fungi, litter, soil ecology


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
Quantitative ecological methods for assessing species diversity usually are based on taxonomic identification of organisms, assembling species lists, and calculating various indices of diversity such as those for species richness (S), diversity (H), dominance (SI) and evenness ( J) from frequency distributions. Such indices then can be used for statistical comparisons between habitats, treatments, etc. (Magurran 1988Go). In practice this approach is useful for taxa that are well known and when individuals can be readily enumerated, but it can be problematic when species cannot be identified or when individuals of a species cannot be readily delimited for enumeration. Ecological studies of microbes in natural environments, particularly fungi, often entail both problems. When the identities of taxa and species composition of communities are not essential, traditional taxonomic approaches to characterizing diversity for ecological investigations of microfungal communities may not have significant advantages over alternative methods. It is not uncommon to encounter fungi in soil- and plant-associated samples that have not yet been taxonomically described or that present other identification problems, often preventing identification below the genus level. The likelihood of encountering unfamiliar and undescribed species is increased when little studied substrates, hosts or habitats are investigated, which may impose limitations on diversity studies in habitats of great interest. Taxonomic data for studies of microfungal diversity based on the traditional methods of dilution plating and subculturing for identification can be limited further when a proportion of isolates fail to grow or sporulate in culture, preventing identification of isolates beyond the category of sterile mycelia.

Nevertheless there are many reasons why indices of fungal diversity may be desirable in ecological investigations. Fungal communities may respond to ecological disturbance agents such as pollutants, fire or clear-cutting well before plant or animal communities and may be useful as early indicators (Durall et al 2005Go, Houston et al 1998Go, Pennanen et al 1996Go, Zak 1992Go). Although taxonomic approaches are typical for investigations of microfungal communities, it sometimes is desirable to obtain estimates of species diversity, richness and evenness of microfungal communities but the identities of fungal taxa and species composition of the communities are not essential. Studies seeking to compare aspects of fungal diversity in relation to ecological or environmental factors may be limited by insufficient taxonomic characterization of fungal species or insufficient taxonomic expertise and resources. In such cases traditional taxonomic approaches to species identification to develop data for ecological indices can be time consuming and potentially less accurate than other approaches. Studies on endophytic fungi isolated from various organs and tissues of plants, for example, frequently report relatively high proportions of both sterile mycelia and novel taxa (Stone et al 2004Go). Although species lists normally comprise the core data in such studies, the objectives often are primarily to investigate ecological differences (e.g. Rodrigues 1994Go). Sometimes combinations of novel species, nonsporulating cultures and limited taxonomic resources necessitate the use of a morphospecies approach or partial taxonomic characterization for fungal biodiversity studies. Arnold et al (2001)Go used a morphospecies approach to characterize diversity, host preference and spatial heterogeneity in endophytic fungi from broadleaf forest trees at a tropical site. Using a method similar to that described by Garland (1996)Go for characterization of patterns of C source use by bacterial communities Zak and Dobranic (1999)Go developed a FungiLog technique based on metabolic diversity for assessing functional diversity of microfungal communities. Ecological studies such as these can reveal patterns in distribution and functional diversity in the absence of traditional systematics. Such data can be useful in evaluating effects of disturbance, land management practices, climate change and a host of ecological factors on fungal communities.

Many mycologists are wary of the use of gross colony morphology as a substitute for taxonomy-based assessment of species composition. A colony morphotype approach has the potential either to over- or underestimate true species diversity, due to variation in colony morphology within individual species or to inability to differentiate a colony morphology common to multiple species (Haldemann and Amy 1993Go, Franklin et al 2001Go, Lebaron et al 1998Go, Quindos et al 1992Go). Furthermore characterization of morphospecies by different investigators may be subject to variation in standardization. While improvements continue to be made in molecular methods for direct estimation of soil microbial diversity (Amann et al 1995Go, Kirk et al 2004Go, Schadt et al 2003Go), such methods also require highly specialized training and equipment and expense may limit their usefulness as preliminary screening tools. There are also a number of difficulties inherent in the restriction analysis of PCR products that also can produce spurious fragments (Egert and Friedrich 2003Go, Webster et al 2003Go). To our knowledge however no studies exist that have compared standard taxonomic methods with alternative methods such as colony morphotyping and PCR-RFLP methods for estimating species diversity. To examine how well diversity estimates based on colony morphospecies correspond to other methods, we undertook this study to compare methods for assessing fungal species diversity. Our objective was to develop a rapid screening method based on standardized, objective criteria for characterization of fungal colony morphotypes, and not requiring specialized training in fungal taxonomy, that could be used as an approximation of fungal species diversity for evaluating soil microfungal communities.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
Sources of litter and soil samples.— – Litter and soil (0–10 cm) and (10–20 cm) core samples were obtained primarily from two sets of Douglas-fir (Pseudotsuga menziesii [Mirbel] Franco) forested and clear-cut test locations in Willamette National Forest, on the western slope of the Cascade Mountains in Linn County, Oregon. Two pairs of sites, Falls Creek and Toad Road, are located respectively at elevations of 536 m and 1220 m; they each previously have been described (Donegan et al 2001Go, Watrud et al 2003Go) and have been the subject of studies that evaluated the effects of postharvest land management practices and edaphic factors on counts of culturable bacteria and saprophytic fungi. At each of the two locations there were eight replicate plots in the forest and seven replicate plots in the adjacent clear-cut. Within forested areas 24 (1 m x 1 m) plots were placed within eight randomly chosen 15 m x 15 m plots that also were isolated randomly within a 0.6 ha area of forest at each site. Three 1 m x 1 m sample plots were systematically placed centrally within each of the NW, NE and SW quadrants of the 15 m x 15 m plots. Within the clear-cuts, a total of 21 (1 m x 1 m) sample plots were located along linear transects; at the Falls Creek site the clear-cut sampling plots were located 5 m apart. At the Toad Creek site the 21 (1 m x 1 m) clear-cut sampling plots were located 20 m apart. Samples were taken from three layers at each plot (litter, 0–10 cm soil and 10–20 cm soil) with a sterile 2.5 cm wide soil corer on each of three sample days at the Falls Creek location and four sample days at the Toad Road location. All samples were kept on ice during transport to the laboratory. Samples were stored overnight at 5 C before subsampling for gravimetric determinations of dry weight after drying at 105 C for 72 h.

Isolation and macroscopic characterization of soil fungi.— – Procedures for sampling and enumeration of soil fungi are shown (FIG. 1Go). Replicate samples from the forested and clear-cut Oregon sites consisted of three layers: surface litter and soil that had been collected at two depths (0–10 cm and 10–20 cm) with a 2.5 cm diam soil corer. Ten mg samples of each litter or soil layer replicate were placed in 90 mL of extraction buffer (0.2% sodium hexametaphosphate and 6um Zwittergent detergent); the samples were shaken 5 min at a setting of 8 on a Multi-Wrist Shaker (Lab-line Instruments Inc., Melrose Park, Illinois). Tenfold serial dilutions of forest litter and soil samples were spread-plated in duplicate onto a dichloran rose bengal (DRB) primary isolation medium (King et al 1979Go) containing 50 µg/mL chlortetracycline and 200 µg/mL streptomycin. After 6 d incubation at 25 C, determinations were made of the abundances of the different colony morphotypes. A standardized reference chart of color photographs and codes of colony morphotypes for the Oregon Cascades Douglas fir litter and soil samples (FIG. 2Go) was developed and used to assign morphotype codes to colonies on DRB plates. This process is analogous to the way Munsell® or other color charts are used to characterize colors of plant or soil sample chemical reactions (Munsell 1977Go). A Dyna-Lume Dyna-Light (Skokie, Illinois), high intensity lamp was used to provide illumination to distinguish morphotypes that were similar in color. Before calculation of ecological indices, raw data for abundances of the various morphotypes on countable DRB plates were normalized on the basis of CFU (gm dry weight)–1 soil or litter.


Figure 1
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FIG. 1. Flow chart of standardized conditions for isolation of fungi from environmental samples. Serial dilutions of forest litter and soil samples were spread aseptically on plates of DRB medium. After incubation at 25 C for 6 d, raw data counts were obtained of the various fungal colony morphotypes. All data were normalized on a dry weight basis before calculation of ecological indices and statistical analyses.

 

Figure 2
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FIG. 2. Color photographs of illustrative colony morphotypes and corresponding letter and color codes. The colony photographs and color code patches can be used to assign colony morphotype codes to fungi grown on DRB medium. After normalization of counts of the different kinds of colony morphotypes that are found in samples on a dry weight basis, ecological indices can be calculated for statistical analyses. Thirty-nine of the colony morphotypes are based on cultures isolated from litter and soil samples derived from forested and clear-cut sites in Willamette National Forest in western Oregon. Five of the isolates (BY, DGY, DT, LG/Y and GG/Y) were derived from soil samples taken in bracken fern stands in the San Bernardino Mountains of California and thus were not included in the determination of ecological indices for the Oregon samples; however DNA extracted from those isolates was included in our PCR-RFLP analyses (FIG. 3Go).

 
Calculation of ecological indices to characterize fungal communities.— – Ecological indices for species richness (S), Shannon index of diversity (H), Simpson’s index of dominance (SI) and species evenness ( J), based on CFU (gm dry wt)–1 of the different colony morphotypes were calculated by standard methods (Magurran 1988Go). Means of the indices were analyzed in SAS by using a repeated-measures MANOVA. Alpha values of P ≤ 0.05 (Wilk’s lambda) were considered to be statistically significant. Illustrative data examples were based on litter and soil samples taken from the Falls Creek and Toad Road Douglas-fir forested and commercially harvested (clear-cut) sites in Willamette National Forest.

Taxonomic identification.— – Fungi isolated on DRB medium (King et al 1977) were subcultured to malt agar (MEA) and Czapek’s with yeast extract (CYA, Pitt 1988Go) and potato-dextrose agar (PDA) for taxonomic analysis. Isolates were identified according to contemporary taxonomic concepts for each group. Species of Penicillia were identified following Pitt (2000) and Fusaria following Gerlach and Nirenberg (1982)Go. Other conidial fungi were identified on the basis of conidium formation and conidiophore structure (Barron 1968Go; Carmichael et al 1980Go; Domsch et al 1980Go, 1993Go; Ellis 1971Go, 1976Go). Isolates that had unique colony morphotypes but which failed to produce conidia or other diagnostic morphological features were assumed to represent separate taxa.

Molecular characterizations of fungal isolates.— – Agar-free samples (5–20 mg fresh weight) of isolates grown on DRB medium were obtained with sterile inoculating loops or scalpels and frozen in 1.5 mL microcentrifuge tubes until the time of DNA extraction and purification by means of a CTAB method (Gardes and Bruns 1993Go). We amplified a section of the ribosomal operon spanning the region between the nuclear small and nuclear large rDNA sequences and which included two internal transcribed sequences (ITS) using a nested PCR system. The four primers used are unique to this laboratory (USEPA, Corvallis, Oregon) and provide good discrimination against plant sequences while amplifying a wide range of fungal sequences (Martin and Rygiewicz 1999Go, 2005Go). The final PCR product was digested separately with three different restriction enzymes (Cfo1, HinF1 and Taq1). Data from all three digests were used for cladistic analysis. Restriction patterns were quantified with the aid of Scanalytics (www.scanalytics.com) RFLP scan gel analysis software and archived in the associated database. Dendrograms were developed with TreeCon software (van de Peer and de Wachter 1994Go) using the Link algorithm, {Gdxy = (Nx+Ny)/(Nx+Ny+Nxy)}, 200 bootstrap iterations and UPGMA (unweighted pair group method using arithmetic averages) clustering (Link et al 1995Go).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
Calculation of ecological indices based on colony morphotypes.— – Morphotype designations were based on macroscopic colony color and texture on DRB medium, following the standardized procedure (FIG. 1Go) for plating and incubation of forest litter and soil samples. Based on pilot studies in which several thousand plates of DRB medium had been inoculated with dilutions of litter and soil samples from environmental chambers used to grow Douglas-fir seedlings in soil obtained in the vicinity of the Toad Road site (Tingey et al 1996Go), 36 commonly observed fungal colony morphotypes that were macroscopically distinct with regard to color, texture or colony margins were designated. Each distinct morphotype was designated by a letter code. Reference photographs of the 36 common colony morphotypes plus five additional ones (BY, DGY, DT, LG/ Y and GG/Y ) isolated from soil associated with bracken fern (Pteridium aquilinum L.) stands in ponderosa pine (Pinus ponderosa P.&C. Lawson) forest sites that were distributed across a natural gradient of atmospheric nitrogenous pollutants, ozone and sulfur (Fenn et al 2000Go, Fenn et al 2003Go, Jordan et al 2005Go) in the San Bernardino Mountains, California, are shown (in the upper portion of FIG. 2Go). Diagrammatic color patches and codes (in the lower portion of FIG. 2Go) correspond to the photographs (in the upper portion of FIG. 2Go) of colonies grown on DRB medium for approximately 1 wk.

Colony morphotype and color reference charts (FIG. 2Go) then were used to enumerate distinct morphotypes on DRB primary soil dilution isolation plates, normalized on dry weight basis g–1 litter or soil, and used to calculate ecological diversity indices (TABLE IGo). No significant differences were found in the ecological indices of samples from the clear-cut and forested areas at the Falls Creek site. In contrast at the Toad Road site highly significant differences were found between the clear-cut and forested litter and soil samples in all four ecological indices (S, H, J and SI) that were examined on each of four sample dates (TABLE IGo). The ecological indices (TABLE IGo) also were calculated based on numbers of taxonomically identified or presumed taxa (all sterile isolates were presumed to be unique taxa). Comparisons between ecological indices based on taxonomic identification also indicated significant differences in species diversity of soil microfungi between clear-cut and forested areas at Toad Road site but not the Falls Creek site (data not shown).


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TABLE I. Ecological indices calculated from fungal colony morphotypes on soil dilution plates from two locations in the Cascade Mountains, Willamette National Forest, Linn County, Oregon

 
Molecular characterization (PCR-RFLP patterns) of different colony morphotypes.— – Data from all three restrictions (Cfo1, HinF1 and Taq1) of the ITS region amplicons were combined to produce 32 distinguishable RFLP pattern sets from 44 isolates representing 4 1 unique colony morphotypes. Saccharomyces cerevisiae and Boletus edulis DNA were used as reference standards to verify the accuracy of the restriction patterns when compared to published sequences. To check for PCR-RFLP reproducibility, many of the patterns (FIG. 3Go) were developed from repeat analyses of the same DNA extract (twice each for 326, 334, 459, 460, 464 and 469). To confirm morphotype reproducibility DNA extracts from different isolates of the same morphotypes were analyzed. The 44 isolates included respectively two DG (454 and 354), MG (451 and 459) and SB (326 and 460). All repeat analyses produced RFLP patterns that were indistinguishable for the same morphotype (FIG. 3Go). Four groups (A–F) were identified in which two or more independent isolates shared the same RFLP pattern sets and showed no cluster-tree distance (FIG. 3Go). An additional 28 patterns were unique to individual isolates from separate colonies (LT 469 was analyzed twice). The largest group (A) contained several isolates with distinct colony morphotypes, all of which had been identified by traditional taxonomic methods as Penicillium spinulosum. Two additional groups (B and C) of isolates included at least one Penicillium species (e.g. P. melinii is grouped with 342 [B] and three P. lividum isolates are grouped [C]). Other Penicillium isolates (P. duclauxii, P. verruculosum, P. arenicola, P. purpurogenum, P. montanense and P. islandicum) each had unique PCR-RFLP patterns. Aspergillus alliaceus and A. flavus also had distinct patterns, as did several isolates that had yeast-like morphologies (Cryptococcus albidus and Rhodotorula graminis). Isolates identified as Mortierella sp. and Humicola grisea respectively made up the bulk of groups E and F. These two were distinguishable only by the molecular weight of the larger HinF1 fragment (ca. 430–450 base pairs) which may not be a significant difference on the agarose gels used for the PCR-RFLP analyses.


Figure 3
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FIG. 3. Cladistic analyses of PCR RFLP patterns from isolates representative of the various fungal colony morphotypes. PCR-RFLP restriction patterns following digestion with Cfo1, HinF1 and Taq1. Most isolates showed unique patterns; however several groups (A–F) had two or more isolates that shared the same pattern.

 
Comparison of colony morphotyping, traditional taxonomic and molecular (PCR-RFLP) approaches to distinguish taxa.— – To evaluate the ability of the colony morphotyping method to distinguish taxa, standard taxonomic identifications and molecular characterization (by multiple RFLP analyses), were attempted on each of the 41 colony morphotypes (FIG. 2Go). Assuming that each of the four culturally different sterile isolates are distinct taxa, the number of taxa corresponded well with the number of RFLPs (32:33 = 97.0%) but less well with the numbers of colony morphotypes (32:41 = 78%). Molecular differentiation of isolates by RFLP analyses also corresponded relatively well with numbers of colony morphotypes (33:41 = 81%). Pairs of identical morphotypes (DG 454 and DG 354, MG 451 and MG 459, and SB 326 and SB2 460) each had identical RFLP pattern sets. However several isolates with distinct colony morphotypes and RFLP pattern sets had the same taxonomic identity (e.g. Fusarium oxysporum isolates PY 339 and FW 346 and Hormonema dematioides isolates SBR 453 and FB 461).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
Colony morphotyping and molecular methods may tend to overestimate species richness as defined by traditional microscopic morphological criteria due to differentiation of morphological variants of the same taxon. However taxonomic identification of micro-fungi to the species level based on microscopic characters and standard cultural methods also can be prone to error. Identification by traditional methods may not even be possible for isolates that fail to sporulate. As described above quantitative colony morphotyping under standardized conditions has been used to calculate ecological indices of species richness, diversity, dominance and evenness for soil microfungi. A number of differences in ecological indices were noted between forested and clear-cut areas in the Cascade Mountains of Oregon. Particularly at the less intensively managed high elevation (Toad Road) site consistent differences in all the indices (S, H, J, SI) were observed between clear-cut and forested areas, regardless of whether numbers of colony morphotypes or numbers of taxa were used to calculate the ecological indices.

At the more intensively managed low elevation (Falls Creek) site, no significant differences were observed in ecological indices of fungal community composition between the clear-cut and forested areas. This was somewhat surprising, given previous observations of significant differences in plant community composition and in bacterial community metabolic profiles between forested and clear-cut areas at that location (Donegan et al 2001Go). It is possible that changes in fungal community composition occurred but were either too small to be detected or did not affect overall diversity.

The correspondences we observed between taxonomic:morphotype, PCR-RFLP:morphotype and taxonomic:PCR-RFLP results (78%, 81% and 97% respectively) support the concept that a standardized quantitative colony morphotyping approach can be used as a viable primary screening method. Our analyses of ecological indices based on colony morphotyping data at two sets of Douglas-fir sites in the western Cascade Mountains suggest that the method may be useful in detecting changes in microfungal community composition after various types of disturbances. Some of the filamentous fungi included in the reference chart (FIG. 2Go) are ubiquitous, cosmopolitan genera that are not unique to forest ecosystems. For example genera such as Penicillium and Aspergillus are common saprophytes; they also include species that may become opportunistic pathogens or allergens of humans. The general approach described herein potentially could be used to create customized reference charts for colony morphotypes of fungi commonly found in specific types of diverse environmental and perhaps indoor and clinical samples. Those unique applications of course would require the availability or definition of specific culture media, culture conditions and development of fungal colony morphotype color reference standards relevant to those particular types of samples of interest. The quantitative colony morphotyping primary screening method we have described is proposed as a primary screening method to identify potential changes in ecological indices of fungal community composition that may occur as a result of natural or anthropogenic disturbances. After taxonomic identification of individual taxa of interest, molecular or other (e.g. immunological or biochemical) methods could be used to detect, monitor and quantify those taxa of specific environmental, academic or clinical interest.

Identical PCR-RFLP patterns among macroscopically morphologically similar but microscopically identical P. spinulosum isolates differentiated as unique morphotypes on the basis of colony color suggests that they might be simply color variants. With additional restriction or sequencing data it is anticipated that P. spinulosum, F. oxysporum and H. dematioides isolates, which were distinguishable by colony morphotyping but which were indistinguishable by taxonomic characters, could be differentiated by molecular methods. However the primary objective of this study was to evaluate the feasibility of a relatively rapid and simple primary screening method for detecting potential changes in fungal community composition. The molecular (PCR-RFLP) and standard taxonomic identification methods used to characterize the isolates described in these studies were included for comparisons of measures of species diversity based on colony morphotyping with traditional taxonomic and to PCR-RFLP fingerprinting approaches to distinguish taxa. If specific morphotypes were to stand out as potential indicators of natural environmental or applied treatments more advanced physiological and molecular methods then could be used to develop molecular, immunological or physiological diagnostics for the presence or absence of specific taxa, genes or enzyme activities.


    ACKNOWLEDGMENTS
 
The information in this document has been financed wholly by the US Environmental Protection Agency. It has been subjected to the agency’s peer and administrative review and it has been approved for publication as an EPA document. Mention of trade names or commercial products does not imply recommendation for use.


    FOOTNOTES
 
Accepted for publication March 3, 2006.

1 Corresponding author. E-mail: Watrud.lidia{at}epa.gov


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