Rhizoctonia Root Rot Diseases Have Declined in Australia Through Continuous 79 Yr of Wheat Cropping

• Journal List
• Appl Environ Microbiol
• v.79(23); 2013 Dec
• PMC3837727

Appl Environ Microbiol. 2013 Dec; 79(23): 7428–7438.

Role of Bacterial Communities in the Natural Suppression of Rhizoctonia solani Bare Patch Disease of Wheat (Triticum aestivum L.)

Chuntao Yin

Department of Plant Pathology, Washington State University, Pullman, Washington, USA^a

Scot H. Hulbert

Department of Plant Pathology, Washington State University, Pullman, Washington, USA^a

Kurtis L. Schroeder

Department of Plant Pathology, Washington State University, Pullman, Washington, USA^a

Olga Mavrodi

Department of Plant Pathology, Washington State University, Pullman, Washington, USA^a

Dmitri Mavrodi

Department of Plant Pathology, Washington State University, Pullman, Washington, USA^a

Amit Dhingra

Department of Horticulture and Landscape Architecture, Washington State University, Pullman, Washington, USA^b

William F. Schillinger

Department of Crop and Soil Sciences, Washington State University, Pullman, Washington, USA^c

Timothy C. Paulitz

USDA Agricultural Research Service, Root Disease and Biological Control Research Unit, Pullman, Washington, USA^d

Received 2013 May 24; Accepted 2013 Sep 17.

Supplementary Materials

Supplemental material

GUID: 519AF563-9637-4879-9742-76AEAC3F9041

GUID: CF387009-AF34-4B66-A2E6-3857A96B165C

Abstract

Rhizoctonia bare patch and root rot disease of wheat, caused by Rhizoctonia solani AG-8, develops as distinct patches of stunted plants and limits the yield of direct-seeded (no-till) wheat in the Pacific Northwest of the United States. At the site of a long-term cropping systems study near Ritzville, WA, a decline in Rhizoctonia patch disease was observed over an 11-year period. Bacterial communities from bulk and rhizosphere soil of plants from inside the patches, outside the patches, and recovered patches were analyzed by using pyrosequencing with primers designed for 16S rRNA. Taxa in the class Acidobacteria and the genus Gemmatimonas were found at higher frequencies in the rhizosphere of healthy plants outside the patches than in that of diseased plants from inside the patches. Dyella and Acidobacteria subgroup Gp7 were found at higher frequencies in recovered patches. Chitinophaga, Pedobacter, Oxalobacteriaceae (Duganella and Massilia), and Chyseobacterium were found at higher frequencies in the rhizosphere of diseased plants from inside the patches. For selected taxa, trends were validated by quantitative PCR (qPCR), and observed shifts of frequencies in the rhizosphere over time were duplicated in cycling experiments in the greenhouse that involved successive plantings of wheat in Rhizoctonia-inoculated soil. Chryseobacterium soldanellicola was isolated from the rhizosphere inside the patches and exhibited significant antagonism against R. solani AG-8 in vitro and in greenhouse tests. In conclusion, we identified novel bacterial taxa that respond to conditions affecting bare patch disease symptoms and that may be involved in suppression of Rhizoctonia root rot and bare batch disease.

INTRODUCTION

Rhizoctonia bare patch and root rot disease, caused by Rhizoctonia solani AG-8, results in major yield limitations in direct-seeded (no-till) cereal crops, as they develop circular or oval patches of stunted plants that produce little or no grain (1). It was discovered in Australia in the 1930s (2) and in the Pacific Northwest (PNW) in the mid-1980s (1, 3). To date, no wheat or barley (Hordeum vulgare L.) cultivars are resistant to Rhizoctonia (4). Furthermore, there are few management strategies for control of Rhizoctonia spp. except for tillage (5), and minimal control is obtained with fungicidal treatment (6–8). Seed treatments may improve seedling health in some cases (9), but a reduction of bare patch disease symptoms has not been observed (7). Growers can reduce damage by reducing greenbridge carryover of the pathogen from grassy weeds and crop volunteers. This carryover is most severe when herbicide treatment is applied right before the crop is planted (10).

Suppression of soilborne pathogens has been described for a number of diseases, including take-all disease of wheat (11), Streptomyces scab disease of potato (Solanum tuberosum L.) (12), Fusarium wilt disease of melons (13), and black rot disease of tobacco (Nicotiana tabacum) (14). In many cases, Pseudomonas species producing antifungal compounds, like phenazine and phloroglucinol, have been implicated in suppression of such pathogens. There are several lines of evidence that Rhizoctonia disease suppression may occur in agricultural fields. Rhizoctonia root rot disease declined to almost nil after 7 to 9 years of continuous wheat cropping in Australia (15). Roget (16) found that Rhizoctonia patch disease development decreased after 5 years of continuous direct-seeded wheat and reached negligible levels after 10 years. A similar Rhizoctonia decline or suppression was also observed in the PNW. Rhizoctonia patch disease sites started to appear 3 years after tillage was stopped at an 8-ha cropping systems rotation study site near Ritzville, WA, and reached a peak in the seventh year, based on annual global positioning system (GPS) mapping of patches. But since then, the areas of patches have declined significantly or even disappeared (17). Cores from the centers of patches were taken into a greenhouse and planted with cycles of monoculture barley over 9 months. Barley was stunted in all cores at the start of the experiment, but over half of the cores did not produce stunting at the end of the experiment (18). In the late 1990s, there was an intensive research effort to understand the basis of Rhizoctonia patch disease suppression in Australia (19–23). The findings suggested that disease suppression may involve mesofauna and macrofauna, or it may have been due to a long-term input of carbon in conservation tillage practices. However, the mechanisms influencing the dynamics of Rhizoctonia are still not well understood.

Soil microorganisms play a major role in soil health and suppression of root diseases (11, 24, 25). The diversity of soil microbial communities is important for the capacity of a soil to suppress soilborne plant diseases (26, 27). In disease-suppressive soils, some of the indigenous microorganisms protect susceptible crops from certain phytopathogens (28). Some isolates of Mitsuaria and Burkholderia inhibited fungal and oomycete growth in vitro and reduced disease severity in infected tomato (Solanum lycopersicum L.) and soybean (Glycine max L.) seedlings (29). Jung et al. (30) demonstrated that Pseudomonas aureofaciens 63-28 induced plant defense systems that led to improved resistance to R. solani AG-4 in soybean seedlings. Barnett et al. (31) suggested that Rhizoctonia patch disease suppression is an interaction among three bacteria, Pantoea agglomerans, Exiguobacterium acetylicum, and Microbacteria sp. Mendes et al. (32) reported that some other bacterial taxa (Proteobacteria, Firmicutes, and Actinobacteria) were consistently associated with suppression of root disease caused by R. solani. These studies indicated that soil disease suppression cannot simply be ascribed to a single microbial group and may involve more biocontrol microbes than previously reported or may even be the synergistic effect of many microbial groups. Therefore, the aim of this study was to compare the composition of the bacterial community inside Rhizoctonia bare patches, outside the patches, and in healthy areas that were previously patches (recovered patches) in wheat at a long-term cropping system study site near Ritzville, WA, that had demonstrated a Rhizoctonia decline. We used pyrosequencing to identify the key component(s) associated with this disease suppression. These trends were verified by using quantitative PCR (qPCR). We also mimicked the transition from conduciveness to disease suppression in greenhouse cycling experiments, and we isolated bacteria to test their biocontrol capabilities.

MATERIALS AND METHODS

Study site, sample collection, and preparation.

This study was conducted at an 8-ha parcel on the Ron Jirava farm (47°8′34″N, 118°28′22″W) located near Ritzville, WA. The traditional cropping system practiced by growers throughout this region is a tillage-based winter wheat-summer fallow rotation by which only one crop is produced every other year. The study site had four replicate blocks, each with 14 different rotation strips, 9 m wide by 152 m long. Mean annual precipitation at the site is 290 mm, and the soil is a Ritzville silt loam (coarse-silty, mixed, superactive, mesic Calcidic Haploxerolls). The soil is >180 cm deep and has no restrictive layers or rocks. The slope at the site is <1%. Rhizoctonia disease bare patches appeared in the rotation strips 3 years after tillage was stopped. From 1999 to 2012, these patches were mapped with a high-resolution GPS device to record the dynamics of patch formation and recovery (33). This study only focused on the continuous annual spring wheat strips to minimize the effects of crop rotation. Samples were collected in April or May of 2008, 2009, and 2010. Both bulk and rhizosphere soil samples were collected from three locations: the center of an active Rhizoctonia disease patch (inside the patch), 1 m outside the same patch (outside the patch), and an adjacent site that did not have a noticeable patch but which had harbored a patch in the previous year (recovered patch). Approximately 1-kg samples of soil from between the rows was taken for the bulk soil samples. For rhizosphere soil samples, 5 to 10 plants were taken with intact roots. Roots with attached rhizosphere soil from wheat plants were cut from the shoot and placed in a 50-ml plastic tube containing 20 ml of sterile distilled water. The tubes were vortexed for 1 min, sonicated for 1 min, and stored at −20°C for further use. The factorial experiment for pyrosequencing of the field samples consisted of three locations (inside, outside, and recovered patches) for 2008 and two locations (inside and outside patches) for 2010 for each of two soil types (bulk and rhizosphere) in each of three replicates. Pyrosequencing of the 2009 samples was not conducted.

DNA extraction, purification, and sequencing.

For bulk soil, DNA was extracted as described previously (34). For rhizosphere soil, 2 ml of the root wash was used for DNA extraction by using an UltraClean soil DNA kit (MO BIO Laboratories, CA) with the alternative protocol for wet soil samples. For bacterial cultures, genomic DNA was extracted from bacteria by using a cetyltrimethylammonium bromide (CTAB) miniprep procedure (35). The DNA was quantified using a Nanodrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA) and stored in a −20°C freezer for subsequent procedures.

The 16S rRNA fragments were amplified from bulk or rhizosphere soil DNA with universal primers. For the 2008 samples, primers were designed to amplify the V3 hypervariable region of bacterial 16S rRNA as described previously (34). The primers were as follows: U342-FC-B, 5′-GCCTTGCCAGCCCGCTCAG CCTACGGGRSGCAGCAG-3′, and U529R-FC, 5′-GCCTCCCTCGCGCCATCAG NNNNN ACCGCGGCKGCTGGC-3′ (the underlined sequences are the 454 Life Science sequencing primers B or A, and the bold letters denote the universal 16S rRNA primers U342-FC-B and U529R-FC). The 5-bp barcode within primer U529R-FC is denoted by 5 italic Ns, and this applied to each 2008 sample. Because technological advances allowed longer sequence reads for the 2010 field samples and cycling experiment samples in the greenhouse, universal primers 27F and 533RAmpTagR were designed to amplify the V1-to-V3 hypervariable regions of 16S rRNA. The primers were as follows: 27F, 5′-CCTATCCCCTGTGTGCCTTGGCAGTCTCAGTCAGAGTTTGATYMTGGCTCAG-3′, and 533RAmpTagR, 5′-CCATCTCATCCCTGCGTGTCTCCGACTCAG NNNNNNNNTCATTACCGCGGCTGCTGGCA-3′, where the underlined sequences are the 454 Life Science sequencing primers B or A, the bold regions are primers targeted to the conserved region of 16S rRNA, the barcode within the reverse primer is denoted by 8 italic Ns, which applied to each soil sample, and the TC after the 8 italic Ns is a linker sequence. A total of 39 barcoded reverse primers are listed in Table S1 of the supplemental material. PCR mixtures consisted of 2 ng of soil DNA, 1× reaction buffer, 0.2 mM deoxynucleotides, 0.25 μM each primer, 5 μl dimethyl sulfoxide, and 0.125 U of Taq DNA polymerase (Invitrogen Corp., CA) in a total volume of 25 μl. PCR was performed using a hot start program, as follows: 80°C for 3 min; 94°C for 5 min; 30 cycles of 94°C for 30 s, 55 to 60°C for 30 s, and 72°C for 30 s; final extension at 72°C for 7 min. Each soil DNA template was amplified in 5 or 6 separate individual reactions. The presence of amplicons was confirmed by gel electrophoresis on a 1.5% (wt/vol) agarose gel, and only specific amplification product was pooled. PCR products were quantified by using a GelDoc quantification system (Bio-Rad). Equimolar amounts (100 ng) of the amplicons of each sample were mixed in a single tube. PCR products were cleaned using the QIAquick PCR purification kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions for pyrosequencing.

To characterize bacterial isolates with antagonistic activity against R. solani AG-8, near-full-length 16S rRNA genes were amplified by PCR from bacterial genomic DNA with conserved primers 8F and 1492R, as described previously (36). The PCR mixtures consisted of 100 ng of purified bacterial DNA, 1× reaction buffer, 0.2 mM deoxynucleotides, 0.4 μM each primer, and 1.25 U of GoTaq DNA polymerase (Promega, Inc., Madison, WI) in a total volume of 25 μl. The amplification was performed using a cycling program that included a 2-min initial denaturation at 94°C followed by 30 cycles of 94°C for 20 s, 55°C for 15 s, and 72°C for 1.5 min, with a final extension at 72°C for 5 min. Amplicons were cleaned with QIAquick PCR purification spin columns (Qiagen, Valencia, CA) and end-sequenced by using the 8F primer (Applied Biosystems, Foster City, CA). The sequences were analyzed by using the Classifier and Seqmatch tools available via the Ribosomal Database Project server (http://rdp.cme.msu.edu).

Barcoded sample pyrosequencing and sequence analysis.

DNA amplicons of the 2008 samples were sequenced as previously described (34). The DNA amplicons of the 2010 samples were sequenced on the genome sequencer (GS) FLX 454 pyrosequencer (Roche) at the University of Idaho. Pyrosequencing reads were processed to remove adapters, barcodes, and primers by using Cross Match (version 1.080806). Base quality clipping was performed using the application Lucy (version 1.20p), and then sequences were aligned by using the SILVA bacterial sequence database and MOTHUR (version 1.12.1). Sequence reads were filtered according to the following criteria: (i) sequences were at least 100 bp in length; (ii) maximum hamming distance of barcode of 1; (iii) maximum number of matching errors to forward primer sequences of 2; (iv) presence of <2 ambiguous bases; (v) a homopolymer run of <7 bp in the sequence; (v) alignment to the SILVA bacterial database within 75 bp of the expected alignment start position as identified by the trimmed mean of all read alignments (trim, 10%); (vii) the read alignment started within the first 5 bp and extended through the read to within the final 5 bp. The RDP Bayesian classifier (Ribosomal Database Project, version 10 [http://rdp.cme.msu.edu/]) was used to assign sequences to phylotypes. Sequences were clustered into operational taxonomic units (OTUs) at a 3% dissimilarity cutoff. To avoid the bias created by analyzing data with different numbers of sequencing reads from each sample, all reported OTU abundances were converted to a relative frequency by dividing the number of reads for any given OTU by the total number of reads obtained for that sample.

Quantitative PCR analysis.

Quantitative PCR was conducted for two bacterial species to validate the results of the sequence analysis and the trends in bacterial populations. These were tested on soil samples from 2008 and 2010 that were subjected to pyrosequencing and also on soil samples from 2009 that were not pyrosequenced. The primers were designed to amplify the specific regions in the 16S rRNA of two species (Acidobacteria subgroup Gp7 and Flavobacterium sp.), and the qPCR methods were described previously (34). The primers were as follows: GP7-F3, 5′-GCTGACAGGAGTTTACAATCCA-3′, GP7-R2, 5′-GCAGCAGTGGGGAATTTTGCG-3′, 859-RT-F2, 5′-ACAATCCATAGGACCGTCATCCTG-3′, and 859-RT-R2, 5′-TGAGACACGGACCAGACTCCTAC-3′. To normalize for differences in DNA extraction and PCR efficiencies for each sample, the universal primers U1406F and U1501R of 16S rRNA were designed to quantify amplification of total bacterial DNA from each sample. The primers for this were as follows: U1406F, 5′-TTGTACACACCGCCCGTCA-3′, and U1501R, 5′-ACGGTTACCTTGTTACGACTT-3′. The fraction of target bacterial DNA was calculated by dividing the amount of target bacterial DNA by the amount of total bacterial DNA in each sample. All reactions were carried out in triplicate.

Cycling experiments in the greenhouse.

To validate the observed shifts of bacterial frequencies in the rhizosphere in the field over time, a cycling experiment was conducted in the greenhouse. This experiment mimicked the planting cycles in the field but compressed the rotation cycle to approximately 1 month instead of 1 year, because of the optimum temperatures in the greenhouse. The soil was collected from the upper 25 cm of the soil profile by using a shovel, from a field adjacent to the study site. The field was managed with conventional tillage with a traditional wheat-fallow rotation. Plastic pots (16 cm in diameter and 18 cm in height) were filled with the soil amended with 1.0% (wt/wt) ground oat kernel inoculum of R. solani AG-8 isolate C1 as described by Paulitz et al. (18). Nine pots filled with natural soil without AG-8 inoculum served as controls. Three seeds of Triticum aestivum L. cv. Alpowa wheat were sown in each pot. A total of 18 pots were incubated in the greenhouse at 15 to 18°C in a dark/light cycle of 12 h and watered two times per week and also with diluted (1:3, vol/vol) Hoagland's solution once a week. After 4 weeks, the plants with intact roots from three pots (with AG-8 inoculum) were harvested, rhizosphere soils were collected as described above, and DNA was extracted for cycle 1 samples. The rhizosphere soils of three plants from each pot served as replicates. The above-ground parts of plants in the remaining 12 pots were cut without disturbing the soils, and the seeds of the same wheat cultivar were replanted in the pots. After another 4 weeks, the rhizosphere soils were collected from three pots (with AG-8 inoculum), and DNA was extracted for cycle 2 samples. Similarly, cycle 3 samples were obtained from the last three pots (with AG-8 inoculum) after four more weeks. 16S rRNA fragments were amplified from rhizosphere soil DNA with the primers 27F and 533RAmpTagR (described above and listed in Table S1 of the supplemental material). DNA amplicons were used for pyrosequencing.

Isolation of bacteria from rhizosphere soil and culture conditions.

To identify bacteria antagonistic to AG-8, bacteria were isolated from rhizosphere soil collected from inside the patches of the Ron Jirava farm. Five plants with intact roots from inside patches were collected and placed into large plastic bags, brought back to the laboratory, and immediately processed. The wheat roots with adhering rhizosphere soil were added to a 50-ml tube containing sterile distilled water, and the tube was vortexed for 1 min and then sonicated in an ultrasonic cleaner for 1 min. The root wash was serially diluted in a 96-well microtiter plate, and the resulting dilutions were plated on ½ TSA medium (1 liter double-distilled water [ddH₂O], 5 g tryptone, 5 g sucrose, and 0.5 g glutamic acid) at 28°C. Representative colony types were picked from the most dilute plate and restreaked to obtain pure colonies. Bacterial isolates were stored in nutrient broth plus glycerol at −80°C.

In vitro antagonistic activities of bacteria against Rhizoctonia solani.

The antagonistic activities of bacterial strains against AG-8 were tested via a dual culture method (37). Paired cultures were incubated at 25°C and scored after 7 days by measuring the diameters of radial growth of AG-8 in the control and in dual cultures. The percent inhibition of radial growth was calculated as follows: 100 × [(R1 − R2)/R1], where R1 was the radial growth of the pathogen in the control and R2 was the radial growth of the pathogen in the dual culture with antagonist. The experiment was repeated three times with three replicates of each treatment. Isolates that showed antagonistic activity against AG-8 were selected for further assays.

Greenhouse biocontrol assays.

To verify antagonistic activity against R. solani AG-8, bacterial isolates that showed antagonistic activity in dual culture assays were tested in the greenhouse. The experiment was performed in two separate assays, with soil collected from the healthy areas, which was sieved through a 0.5-cm-mesh screen. Part of the soil was pasteurized at 60°C for 30 min to reduce interference from other nonsporulating soilborne microorganisms. Both soils were air dried at room temperature and were amended with 1.0% (wt/wt) ground oat kernel inoculum of AG-8. Fresh bacterial cultures grown on ½ TSA plates were scraped, suspended in double-distilled water, and centrifuged for 3 min at 13,000 rpm. The pellet was resuspended in sterile ddH₂O and adjusted to 1 × 10⁸ CFU/ml. Plastic cones (2.5 cm in diameter and 16.5 cm long) were filled with 70 g of Rhizoctonia-inoculated soil and 20 ml of the bacterial cell suspension. Soil samples amended or not amended with oat kernel inoculum served as controls. Three wheat seeds (cultivar Alpowa) were sown in each cone. Cones were arranged in a randomized complete block design in plastic racks and incubated in the controlled-environment greenhouse as described above. After 3 weeks, the seedlings were removed from the cones, the roots were washed, the plants were evaluated for Rhizoctonia patch disease root rot severity on a scale of 0 to 8, and root length was measured as described previously (10, 38). Each treatment had 10 replicates, and the experiment was conducted twice.

Statistical analysis.

Data analyses were performed using the general linear models (GLM) procedures within the SAS statistical software package (SAS Institute, Inc., Cary, NC). The numbers of individual OTUs per sample were normalized by dividing the number of OTUs by the total number of sequences in each sample. These frequency data were used for statistical analysis. Multiple comparisons were performed using Tukey's test. Significance was accepted at an α level of ≤0.05. The Shannon diversity index, richness, abundance, and evenness of OTUs were calculated as described previously (34). Greenhouse biocontrol assay data were analyzed with STATISTIX 8.0 software (Analytical Software, St. Paul, MN). Differences in root disease or root lengths among treatments were determined by standard analyses of variance, and mean comparisons among treatments were performed by using Fisher's protected least significant difference (LSD) test (P ≤ 0.05).

RESULTS

Bacterial community structure and composition.

A total of 72,360 high-quality reads were generated in 2008, providing 2,070 to 5,746 sequences (150 to 220 bp in length) for each soil sample, and these were assembled into 345 OTUs by using a 3% dissimilarity cutoff. A total of 35,922 high-quality reads were generated in 2010, providing 2,566 to 3,441 sequences (350 to 400 bp in length) for each sample, and these were assembled into 697 OTUs. Among all the phyla in 2008, Proteobacteria was the most abundant taxonomic group, followed by Bacteroidetes, Actinobacteria, and Acidobacteria (Fig. 1). In 2010, the most abundant taxonomic group was Actinobacteria, followed by Proteobacteria and Bacteroidetes (Fig. 2).

Frequencies of bacterial phyla in three locations (inside or outside the patches and in recovered patches) in 2008 (with a 3% dissimilarity cutoff).

Frequencies of bacterial phyla in two locations (inside or outside the patches) in 2010 (with a 3% dissimilarity cutoff).

The diversity of bacterial communities was determined based on the Shannon diversity index, along with richness, evenness, and abundance (Table 1). In 2008, the diversity was higher in the bulk soil than in the rhizosphere soil from inside the patches, but the abundance was higher in the rhizosphere soil. Within the bulk soil of 2008, the abundance was significantly lower in the recovered patches than in the other two locations. In 2010, there was no effect of location on bacterial diversity, evenness, or richness, but inside the patches, the abundance was higher in the rhizosphere than in the bulk soil.

Table 1

Diversity, richness, abundance, and evenness indices for 2008 and 2010 field samples ^a

Soil type	Sample source	Shannon diversity index b		Richness index c		Abundance d		Evenness e
		2008	2010	2008	2010	2008	2010	2008	2010
Bulk soil	Inside the patch	4.20 a	4.84 a	207	340	2,149 ab	1,451 b	0.79 ab	0.83
	Outside the patch	4.07 a	4.96 a	186	365	1,744 b	1,570 ab	0.78 ab	0.84
	Recovered patch	4.32 a		178		1,152 c		0.83 a
Rhizosphere soil	Inside the patch	3.24 b	4.83 a	170	322	2,779 a	1,763 a	0.63 c	0.83
	Outside the patch	3.64 ab	4.84 a	183	330	2,216 a	1,593 ab	0.70 b	0.83
	Recovered patch	3.83 ab		201		2,917 a		0.72 b

The higher abundance levels of bacteria in the rhizosphere soil or in soil from different locations (inside the patch, outside the patch, and the recovered patch) were explored by comparing relative frequencies of all OTUs (Tables 2 and ​ 3). We noted that a few taxa (Flavobacterium, Pedobacter, Duganella, Acidobacteria subgroup Gp4, and Gemmatimonas) included multiple OTUs. Each OTU may represent different species or strains, but they cannot be differentiated in the RDP databases. Table 2 lists bacterial taxa with higher abundances of bacterial OTUs in the rhizosphere soil than in bulk soil (P ≤ 0.05) in 2008 and 2010 field samples (inside of patch, outside of patch, and recovered patch). Pseudomonas, Flavobacterium, Variovorax, Burkholderia, and Pedobacter showed a similar trend of a significantly higher frequency in the rhizosphere soil than in the bulk soil in both years. However, a number of taxa, including Microbacterium, Phyllobacterium, and one in the Sphingobacteriales order, were significantly more abundant in the rhizosphere soil in 2008 only, and other taxa, such as a few genera in the Oxalobacteraceae family (Duganella, Herminiimonas, and Herbaspirillum), Mesorhizobium, Ralstonia, Chitinophaga, and Gemmatimonas, were more abundant in the rhizosphere soil in 2010 only (Table 2).

Table 2

Bacterial taxa with higher abundance in rhizosphere soils than bulk soil in the 2008 and/or 2010 field samples

Taxa with a significantly a higher abundance in rhizosphere soil than bulk soil in b :
2008		2010
Family	Genus	Family	Genus
Pseudomonadaceae	Pseudomonas*	Pseudomonadaceae	Pseudomonas*
Flavobacteriaceae	Flavobacterium*	Flavobacteriaceae	Flavobacterium* (OTU258, OTU367)
Comamonadaceae	Variovorax*	Comamonadaceae	Variovorax*
Burkholderiaceae	Burkholderia*	Burkholderiaceae	Burkholderia*
Sphingobacteriaceae	Pedobacter*	Sphingobacteriaceae	Pedobacter* (OTU26, OTU52, OTU380)
Microbacteriaceae	Microbacterium	Oxalobacteraceae	Duganella (OTU4)
			Duganella (OTU200)
			Herminiimonas
			Herbaspirillum
Phyllobacteriaceae	Phyllobacterium	Phyllobacteriaceae	Mesorhizobium
Sphingomonadaceae	Sphingomonas	Burkholderiaceae	Ralstonia
		Chitinophagaceae	Chitinophaga
		Gemmatimonadaceae	Gemmatimonas (OTU13, OTU1597)

Table 3

Relative abundances of bacterial taxa that differed based on patch sampling area (inside, outside, or recovered) in rhizosphere soil from field samples

Family a	Genus b	Year	Frequency (×10−3) c
			Inside the patch	Outside the patch	Recovered patch
Chitinophagaceae	Chitinophaga* (OTU38)	2008	59.07 a	39.53 b
		2010	4.88 a	1.17 b
Comamonadaceae	Variovorax*	2008	26.59 a	17.67 b
		2010	51.41	42.9
Sphingobacteriaceae	Pedobacter (OTU380)*	2008	31.67 a	17.43 b
		2010	3.02 a	1.88 b
	Pedobacter (OTU52)*	2010	3.21 a	1.26 b
Cytophagaceae	Dyadobacter	2008	7.81 a	1.62 b
Flavobacteriaceae	Flavobacterium	2008	26.6 a	2.81 b
Microbacteriaceae	Microbacterium	2008	2.88 a	0.92 b
Moraxellaceae	Acinetobacter	2008	27.92 a	1.98 b
Phyllobacteriaceae	Phyllobacterium	2008	5.16 a	0.29 b
Flavobacteriaceae	Chryseobacterium (OTU437)	2010	3.64 a	0.23 b
Oxalobacteraceae	Duganella (OTU4)	2010	12.32 a	4.49 b
	Massilia (OTU1244)	2010	1.83 a	0 b
Pseudomonadaceae	Pseudomonas (OTU9)	2010	12.07 a	2.88 b
Sphingobacteriaceae	Mucilaginibacter	2010	1.71 a	0.2 b
Acidobacteria	Acidobacteria subgroup Gp3	2008	4.43 b	10.67 a	7.44 a
		2010	0.57 b	2.51 a
Acidobacteria	Acidobacteria subgroup Gp7*	2008	1.8 c	2.45 b	6.85 a
		2010	0 b	1.67 a
Burkholderiaceae	Burkholderia*	2008	4.12 b	24.98 a	17.95 a
		2010	13.8	18.41
Phyllobacteriaceae	Mesorhizobium*	2008	3.7	4.11	5.14
		2010	7.56 b	13.81 a
Xanthomonadaceae	Dyella	2008	0.37 b	0.48 b	1.54 a
		2010	3.02 b	6.7 a
Acidobacteria	Acidobacteria subgroup Gp1	2008	9.38 b	21.1 a
Actinomycetaceae	Actinobacteria	2008	4.78 b	12.96 a
Acidobacteria	Acidobacteria subgroup Gp4 (OTU170)	2010	1.29 b	2.69 a
	Acidobacteria subgroup Gp4 (OTU788)	2010	0 b	0.83 a
Flavobacteriaceae	Flavobacterium (OTU258)	2010	6.05 b	18 a
	Flavobacterium (OTU367)	2010	5.1 b	15.48 a
Gemmatimonadaceae	Gemmatimonas (OTU107)	2010	0.36 b	1.69 a
	Gemmatimonas (OTU1105)	2010	1.02 b	4.06 a

Table 3 lists the bacterial distributions in the rhizosphere soil that were affected by sampling location. Taxa within Chitinophaga, Variovorax, and Pedobacter were detected at greater abundance inside the patches in both years. Other bacteria, such as from taxa within Dyadobacter, Flavobacterium, Microbacterium, Acinetobacter, and Phyllobacterium, were more abundant inside the patches in 2008 only. Chryseobacterium, Oxalobacteraceae (Dunganella and Massilia), Pseudomonas, and Mucilaginibacter were more abundant inside the patches in 2010. On the other hand, Acidobacteria subgroup Gp3, Acidobacteria subgroup Gp7, Burkholderia, Mesorhizobium, and Dyella were observed at higher frequencies outside the patches in both years and in recovered patches in 2008 (Table 3). Some bacteria, such as Acidobacteria subgroup Gp1 and Actinobacteria, were more abundant outside the patches in 2008. Acidobacteria subgroup Gp4, Flavobacterium, and Gemmatimonas were abundant outside the patches in 2010 (Table 3).

Quantitative PCR.

In order to validate the results of the pyrosequencing, the abundance of two bacterial species (Flavobacterium and Acidobacteria subgroup Gp7) were determined with qPCR in rhizosphere soil DNA extracts from 2008, 2009, and 2010 field samples. Flavobacterium and Acidobacteria subgroup Gp7 were selected because Flavobacterium was abundant in the rhizosphere soil and Acidobacteria subgroup Gp7 was abundant outside the patches and in the recovered patches. The results showed that the DNA concentration of Acidobacteria subgroup Gp7 was higher in recovered patches in 2008 and 2009 and outside the patches in 2010 (Fig. 3B), confirming the trend found with the pyrosequencing data (Fig. 3A), but the DNA concentration was lower outside the patches in 2009. For Flavobacterium, the highest concentration of DNA was found inside the patches in 2008, while the highest concentration of DNA of Flavobacterium shifted to outside the patches in 2010 (Fig. 3D), which was also consistent with the pyrosequencing frequency results (Fig. 3C). The DNA concentration of Flavobacterium in 2009 was not significantly different among samples from inside the patch, outside the patch, and the recovered patch (Fig. 3D).

Frequencies of bacterial species in the rhizosphere soil of three locations (inside and outside the patches and in recovered patches) in 2 or 3 years (2008 and 2010, and also 2009 for some species). (A) Frequency of Acidobacteria subgroup Gp7, measured by pyrosequencing; (B) amount of Acidobacteria subgroup Gp7, measured by qPCR; (C) frequency of Flavobacterium sp., measured by pyroseqencing; (D) amount of Flavobacterium sp., measured by qPCR. Bars with different letters in the same year indicate statistically significant differences according to Tukey's test (P ≤ 0.05). The values are means of three replicates.

Greenhouse cycling experiments.

To duplicate bacterial shifts in the rhizosphere soil in field samples, cycling experiments were conducted in the greenhouse to mimic field treatments, as described in Materials and Methods. After the first cycle, severe wheat stunting was observed in pots with AG-8 inoculum compared with the control pots without AG-8 inoculum. After the second cycle, mild wheat stunting was still observed in pots with AG-8 inoculum. However, after the third cycle, wheat in the pots with AG-8 inoculum no longer showed stunting, similar to wheat growth in the control pots (data not shown). Similar disease suppression phenomena were observed in previous greenhouse tests (18). This suggested that soils in the pots with AG-8 inocula had become suppressive after 3 cycles of wheat growth in the greenhouse. To monitor the bacterial community changes, pyrosequencing was conducted to characterize bacterial organisms in the rhizosphere soil after each cycle. A few genera (Massilia [OTU288], Duganella, and Herbaspirillum [OTU94] in the family Oxalobacteraceae) became more abundant in the rhizosphere soil with increasing cycles of wheat seedling growth (Table 4). A number of other taxa, including Chryseobacterium (OTU437), Chitinophaga, Pedobacter, and Pseudomonas (OTU9), increased dramatically in the second cycle, and then in the third cycle they decreased a little or to the level of the first cycle. Interestingly, all bacteria mentioned above showed significantly higher abundance in the rhizosphere soils inside the patches than outside the patches (Table 4). Furthermore, a strong correlation was observed between qPCR and pyrosequencing results for Flavobacterium (Fig. 4A and ​ B).

Table 4

Frequencies of bacterial taxa in rhizospheres of field samples versus greenhouse cycling experiment samples

Family	Genus	Frequency (×10−3) of genus in a :
		Greenhouse samples			Field samples (in 2010)
		Cycle1	Cycle2	Cycle3	Inside the patch	Outside the patch
Oxalobacteraceae	Massilia (OTU288)	1.21 c	5.50 b	14.89 a	2.40 a	0.20 b
	Duganella (OTU4)	1.14 c	22.89 b	32.36 a	12.32 a	4.49 b
	Herbaspirillum (OTU94)	1.14 b	5.88 b	72.82 a	7.27 a	0 b
Flavobacteriaceae	Chryseobacterium (OTU437)	0 c	65.54 a	15.21 b	3.64 a	0.23 b
Chitinophagaceae	Chitinophaga (OTU38)	2.50 b	7.50 a	5.60 a	4.88 a	1.17 b
Sphingobacteriaceae	Pedobacter (OTU380)	3.85 b	11.86 a	3.27 b	3.02 a	1.88 b
Pseudomonadaceae	Pseudomonas (OTU9)	1.71 b	6.16 a	5.64 a	12.07 a	2.88 b

Bacterial frequencies in the rhizosphere soil in the cycling experiment in the greenhouse. (A) Frequency of Flavobacterium sp., measured by pyroseqencing; (B) amount of Flavobacterium sp., measured by qPCR. Bars with different letters indicate statistically significant differences according to Tukey's test (P ≤ 0.05). The values are means of three replicates.

Antifungal capabilities of bacteria in vitro.

To identify bacterial taxa that may be involved in soils naturally suppressive to R. solani, 48 bacterial isolates were obtained from the rhizosphere soil from inside the patches that represented the most abundant colony types. In dual culture tests, six isolates significantly inhibited the radial mycelial growth of AG-8 (Table 5). The percent inhibition of radial growth (PIRG) values ranged from 34.4% to 59.3%. The highest PIRG value (59.3%) was observed with isolate 38, and the lowest (34.4%) was recorded with isolate 44 (Fig. 5B to ​ G and Table 5). These six isolates' identities were determined from the 16S rRNA sequences (Table 5). Three isolates (isolates 31, 37, and 38) were considered the same species (Chryseobacterium soldanellicola) because their 16S rRNA sequences showed 100% identity, similar antagonistic activity on petri dishes, and similar gliding motility on the ¼ PDA medium (Fig. 5C, ​ D, and ​ E). These isolates displayed 100% sequence identity to OTU437 (Chryseobacterium) from the field samples and cycling experiments. Isolate 43 was also identified as C. soldanellicola according to the 16S rRNA sequence, but the gliding motility on the ¼ PDA medium was different from the above three (Fig. 5F). The other two were Pseudomonas (isolate 25) and Pedobacter (isolate 44), which displayed 100% sequence identities to OTU9 (Pseudomonas) and OTU26 (Pedobacter), respectively (Table 5). The remaining 42 bacterial isolates did not exhibit significant inhibition of the radial growth of AG-8.

Table 5

Inhibition of radial growth of R. solani in dual culture by selected bacteria

Isolate ID no.	Genus a	% inhibition of radial growth b
Control	R. solani AG-8	0 c
25	Pseudomonas sp. (OTU9)	39.9 ± 7.7 ab
31	Chryseobacterium soldanellicola (OTU437)	53.1 ± 13.6 ab
37	Chryseobacterium soldanellicola (OTU437)	56.0 ± 20.3 ab
38	Chryseobacterium soldanellicola (OTU437)	59.3 ± 15.0 a
43	Chryseobacterium soldanellicola (OTU18)	54.7 ± 22.7 ab
44	Pedobacter sp. (OTU26)	34.4 ± 9.7 b

Dual culture assays for in vitro inhibition of growth of R. solani AG-8 by bacterial isolates on ¼ PDA medium 7 days after incubation. (A) Control (only AG-8); (B) Pseudomonas sp. (isolate 25) and R. solani AG-8; (C) C. soldanellicola (isolate 31) and R. solani AG-8; (D) C. soldanellicola (isolate 37) and R. solani AG-8; (E) C. soldanellicola (isolate 38) and R. solani AG-8; (F) C. soldanellicola (isolate 43) and R. solani AG-8; (G) Pedobacter sp. (isolate 44) and R. solani AG-8.

Biocontrol capabilities of bacterial isolates in greenhouse assays.

All six antagonists (isolates 25, 31, 37, 38, 43, and 44) were tested to determine their biological control capability against AG-8 in the greenhouse. In the natural soil (nonpasteurized), treatments with three C. soldanellicola isolates (isolates 31, 37, and 38) significantly reduced disease caused by AG-8 (Table 6). The root rot rating decreased and root length increased in treated soils compared with the nonpasteurized AG-8-inoculated control. But Pseudomonas sp. (isolate 25), Chryseobacterium (isolate 43), and Pedobacter sp. (isolate 44) did not show significant disease reductions in the greenhouse in natural soil. Treatment with Pseudomonas sp. slightly increased disease severity (Table 6). In pasteurized soil, the root rot rating for treatments of C. soldanellicola (isolate 43) and Pseudomonas sp. isolates decreased slightly compared to the AG-8-inoculated control. C. soldanellicola (isolates 38 and 43) increased the root length (Table 6). However, treatments with two C. soldanellicola isolates (isolate 31 or 37) in pasteurized soil did not result in significant suppression of disease. The plants in the soil treated with only bacteria showed a similar phenotype as the control soil (without the AG-8 inoculum) (Table 6).

Table 6

Effects of different treatments of bacterial cultures in greenhouse assays on the suppression of root rot of wheat plants caused by R. solani AG-8

Presence of R. solani	Treatment		Bacterium (isolate no.)	Root rot rating a	Root length (mm) a
	Nonpasteurized soil	Pasteurized soil
−	+		None	0.6 e	14.9 a
−	+		Pseudomonas sp. (25)	0.6 e	14.4 ab
−	+		Chryseobacterium soldanellicola (31)	1.0 e	14.4 ab
−	+		Chryseobacterium soldanellicola (37)	0.5 e	14.6 a
−	+		Chryseobacterium soldanellicola (38)	1.1 e	13.6 abc
+	+		None	6.4 ab	9.1 e
+	+		Pseudomonas sp. (25)	6.7 a	7.1 f
+	+		Chryseobacterium soldanellicola (31)	4.2 d	12.6 bcd
+	+		Chryseobacterium soldanellicola (37)	4.9 c	11.5 d
+	+		Chryseobacterium soldanellicola (38)	4.0 d	12.4 cd
+	+		Chryseobacterium soldanellicola (43)	5.8 b	11.5 d
+	+		Pedobacter sp. (44)	5.9 b	11.2 d
−		+	None	0.3 d	13.4 a
−		+	Pseudomonas sp. (25)	0.5 d	14.3 a
−		+	Chryseobacterium soldanellicola (31)	0.5 d	14.3 a
−		+	Chryseobacterium soldanellicola (37)	0.3 d	14.5 a
−		+	Chryseobacterium soldanellicola (38)	0.3 d	14.0 a
+		+	None	6.8 ab	8.7 cd
+		+	Pseudomonas sp. (25)	6.2 c	8.8 cd
+		+	Chryseobacterium soldanellicola (31)	6.9 a	7.7 d
+		+	Chryseobacterium soldanellicola (37)	6.5 bc	9.9 bc
+		+	Chryseobacterium soldanellicola (38)	6.4 bc	10.9 b
+		+	Chryseobacterium soldanellicola (43)	6.2 c	11.5 b
+		+	Pedobacter sp. (44)	6.7 abc	10.3 bc

DISCUSSION

We have reported here the first detailed study of the bacterial communities associated with Rhizoctonia patch disease-induced decline and the first example of this phenomenon outside Australia (16). We found a number of taxonomic groups that were associated with the rhizosphere of diseased plants, with two predominating: the phylum Bacteroidetes (families Sphingobacteriaceae and Flavobacteriaceae) and the class Betaproteobacteria (family Oxalobacteraceae). In 2008, the most dominant genus was Chitinophaga, a member of the class Sphingobacteria, a gliding chitin-decomposing myxobacterium. It has been isolated from a number of soils in South Korea (39) and was the most dominant taxa in four soils from North and South America (40). Within the Bacteroidetes, we found the gliding bacteria Flavobacterium and Chryseobacterium were dominant in the rhizospheres of diseased plants. Previous work with soil from western Washington State reported that the abundance of Chryseobacterium and Flavobacterium increased significantly in the rhizosphere of take-all disease-affected plants (41). This suggests that both root pathogens (Gaeumannomyces graminis var. tritici and Rhizoctonia solani) promote similar bacteria, possibly from exudates leaking from diseased roots. However, Chryseobacterium isolates displayed no ability to inhibit Gaeumannomyces graminis var. tritici in vitro and did not interfere with the antagonism caused by an isolate of Pseudomonas antagonistic to take-all disease (42). In this study, we were able to isolate a number of strains of Flavobacterium and Chryseobacterium from the rhizosphere soils of diseased plants and demonstrated that three isolates (isolate 31, 37, and 38) of Chryseobacterium could inhibit R. solani in vitro and reduce Rhizoctonia patch disease in inoculated natural soil but not in pasteurized soil in greenhouse experiments (Tables 5 and ​ 6). It is possible that these isolates may interact with other microorganisms in the natural soil and suppress Rhizoctonia patch disease. Benítez and Gardener (29) successfully used sequence-based molecular markers (terminal restriction fragment length polymorphisms) to isolate novel bacterial genera, Mitsuaria and Burkholderia, which were involved in the suppression of damping-off disease pathogens. Our current results further supported that identification and isolation of functionally important microbes from diverse microbial communities by use of sequence-based molecular screening is a low-cost and powerful approach to develop sustainable disease management. Additionally, taxa as dominant communities in the rhizosphere of wheat, in association with phloroglucinol-producing Pseudomonas fluorescens genotypes, have been described (41, 42). In both studies, Flavobacterium isolates were identified by molecular techniques. In the mid-1990s, J. Raaijmakers and D. M. Weller (43) also found that Flavobacterium became a dominant component of the wheat rhizosphere after successive cycling or monocropping experiments in the greenhouse. Flavobacterium has been identified as a common component in the rhizospheres of barley (44), turfgrass (45), and tomatoes (46). There is extensive literature on this group in terms of bioremediation and biodegradation and for breakdown of mycotoxins. These bacteria are found in aquatic habitats, and some are fish pathogens. They have served as models for study of the molecular basis of gliding. There have also been some reports of Flavobacterium as a biocontrol agent for Verticillium dahliae (47), Colletotrichum (48), sunflower (Helianthus annuus L.) pathogens (49), and Botrytis (50).

In 2008, the total diversity was higher in the bulk soil than in the rhizosphere soil from inside the patches; this trend was not seen in 2010. However, inside the patches, bacterial abundance was higher in the rhizosphere than in the bulk soil for both years (Table 1). This suggested that there is a higher diversity of niches in the bulk soil but that the rhizosphere selects for a narrow diversity of taxa, with higher populations supported by the large amounts of exudates. In a study correlating biomass productivity with rhizosphere communities on wheat grown in raw soil, OTUs of Duganella and Janthinobacterium, two genera of the Oxalobacteriaceae, were positively correlated with plant biomass, along with Pseudomonas (51). OTUs of Chryseobacterium and Enterobacterium were negatively associated. However, those investigators did not look at pathogens in the system, and it is possible that pathogens caused the reduction in biomass and that these genera were associated with diseased roots, as we found in our study.

The rhizosphere of recovered or healthy patches may represent a more stable community with a higher diversity. We found Acidobacteria subgroup Gp7 and Dyella at higher frequencies in the recovered patches in 2008 (Table 3). Dyella was first described as a genus within the family Xanthomonadaceae when it was isolated from soil in 2005 (52) and subsequently from the rhizosphere of bamboo (53), from the nodules of Lespedeza sp. (54), and also as a seed-borne endophyte of rice (55). Dyella japonica was shown to comigrate with Burkholderia on the hyphae of Lyophyllum, a genus of edible mycorrhizum-forming mushrooms, in soil microcosms (56) and was selected in the mycosphere of the basidiomycetes. On the contrary, the rhizosphere of diseased plants had less diversity, as it was dominated by an abundance of copiotrophic, fast-growing bacteria that utilize the exudates leaking from infected roots. This concept was demonstrated in our cycling experiments in the greenhouse. The soils inoculated with AG-8 became suppressive after three cycles of wheat growth under direct seed planting conditions. Interestingly, we found that a few taxa of Chryseobacterium and also Pseudomonas became more prevalent in the rhizosphere soil with increasing cycles (Table 4). Compared to the microorganism community in the field samples, these taxa showed higher abundances in the rhizospheres of diseased plants. This indicated that our cycling experiments in the greenhouse could duplicate some taxonomic shifts in bacteria that operate at the field level. Kyselková et al. (28) found that taxa of Pseudomonas and Bacteroidetes were higher in soil suppressive to tobacco black rot caused by Thielaviopsis basicola when they used a microarray based on 16S RNA, similar to our results. We further demonstrated that Chryseobacterium and Pseudomonas exhibited inhibitory activities against R. solani in vitro or reduced Rhizoctonia disease in inoculated natural soils (Table 5 and ​ 6). These findings indicate that these organisms may play important roles in the transition of soil from conducive to suppressive conditions. Suppression of soilborne disease has been well documented for declines in take-all disease, in which Pseudomonas colonizes microsites on diseased roots and produces antibiotics that lead to disease suppression (41, 57, 58). Pseudomonas comprised 2 to 5% of sequences from the rhizosphere in our study. Phenazine-producing Pseudomonas has been found at high frequencies in samples taken at this location, as reported elsewhere (59). There are at least four groups of Pseudomonas that have been identified from phylogenetic studies of a number of genes (60), but the species cannot be distinguished by the pyrosequencing method used in our study. A few Oxalobacteraceae (Massilia, Duganella, and Herbaspirillum) and Chitinophaga also increased significantly in the rhizospheres of diseased plants in the field and with increasing cycles. Whether these taxa have similar inhibition abilities is unclear. It is possible that some of them may interact with Chryseobacterium to suppress Rhizoctonia patch disease. However, much more work needs to be done to address their functions. Additionally, Pedobacter and Variovorax were also common in the rhizosphere of wheat plants inside the patches in our study (Table 3), the latter comprising 1 to 5% of the sequences.

In conclusion, we have identified members of a highly complex bacterial community that may be involved in the suppression of Rhizoctonia bare patch and root rot disease of wheat, as documented in a 14-year study (17). If early shifts of community structure are indicative of the later development of suppression, such shifts can be used as a tool to test crop rotations and cultural techniques that may enhance and hasten the development of disease suppression. Can this suppression develop faster than in 5 to 7 years? What are the implications for wheat growers? Better knowledge of this phenomenon may result in recommendations for cultural practices and crop rotations that will enhance this natural disease suppression. Once it is established, growers will not need to provide any chemical inputs, or they can rely on resistant cultivars, which have eluded plant breeders. This may provide an impetus for more growers to adapt direct seed or no-till conservation agriculture methods, reducing the loss of the valuable soil resource.

Supplementary Material

ACKNOWLEDGMENTS

This work was supported by Washington State University, the USDA Agricultural Research Service, the Columbia Plateau PM₁₀ Project, and the Solutions to Economic and Environmental Problems (STEEP) Project.

We thank Suresh Iyer and Matt Settles at the University of Idaho and Qingsheng Zhang for pyrosequence and data analysis. We gratefully acknowledge wheat grower Ron Jirava for providing the field site and Washington State University agricultural research technicians Harry Schafer, Timothy Smith, and Steven Schofstoll for their excellent technical assistance.

Footnotes

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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3837727/

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