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Agriculture (Poľnohospodárstvo), 62, 2016 (2): 52−61 DOI: 10.1515/agri-2016-0006 Original paper MONITORING OF RHIZOSPHERE BACTERIAL COMMUNITIES IN SOIL WITH SEWAGE SLUDGE ADDITION USING TWO MOLECULAR FINGERPRINTING METHODS: DO THESE METHODS GIVE SIMILAR RESULTS? 1* 1 2 KATARÍNA ONDREIČKOVÁ , ALŽBETA ŽOFAJOVÁ , MICHAELA PILIAROVÁ , 1 1 JOZEF GUBIŠ , MARTINA HUDCOVICOVÁ National Agricultural and Food Centre – Research Institute of Plant Production, Piešťany, Slovak Republic University of SS. Cyril and Methodius in Trnava, Slovak Republic ONDREIČKOVÁ, K. ‒ ŽOFAJOVÁ, A. ‒ PILIAROVÁ, M. ‒ GUBIŠ, J. ‒ HUDCOVICOVÁ, M.: Monitoring of rhizos - phere bacterial communities in soil with sewage sludge addition using two molecular fingerprinting methods: Do these methods give similar results? Agriculture (Poľnohospodárstvo), vol. 62, 2016, no. 2, pp. 52–61. In this study, bacterial genetic diversity from the rhizosphere of barley and wheat were studied. The plants were sown in pots with aliquot amount of 15 t/ha concentration of soil additive derived from sewage sludge and agricultural by - products represented by wastes from grain mill industry and crushed corn cobs. The plants sown in pots without the ad - dition of soil additive represented control samples. The rhizosphere samples were collected on two dates (plant flower- ing and maturity) and the composition of bacterial communities were detected using two molecular fingerprinting methods – automated ribosomal intergenic spacer analysis (ARISA) and terminal restriction fragment length polymor - phism (T-RFLP). Microbial biomass expressed as the amount of metagenomi cs DNA was higher in soils with addition of soil additive, except during maturity stage in barley rhizosphere. Nevertheless, statistically significant differences between control and sludge samples were not detected in any case. Similarly, no changes were detected in the com - position of bacterial community between control and sludge samples in barley and wheat rhizosphere by using cluster analysis. Only minor temporal changes in the composition of bacterial community between flowering and maturity periods were observed. These changes were related to the samples collected in the plant maturity stage. In this stage, plants were completely mature and their impact on the rhizosphere bacterial communities in the form of root exudates was limited. Statistically significant differences between ARISA and T-RFLP methods were detected in all measured values of diversity indices. Despite these differences, both methods gave results leading to similar conclusi ons. Key words: ARISA, bacterial community, genetic diversity, rhizosphere, sewage sludge, T-RFLP Sewage sludge is the final product of wastewater 223/2001 Z. z. as waste. An advantage of sewage treatment process and its production in the Slovak sludge application to agricultural land is its use as a Republic has increased from 54,000 tons in 1998 to valuable source of plant micro- and macronutrients, 58,706 tons in 2012 (Ministry of Environment of and organic matter (Moffett et al. 2003). The high the Slovak Republic). This sludge is mechanically content of organic matter and the favourable ratio dewatered and anaerobically stabilized, allowing its of C:N (18:1) lends relevance to the use of sewage use as a raw material in the production of compost, sludge as a fertiliser substrate. On the other hand, or direct application to agricultural soil. Sludge sewage sludge may be a source of chemical (heavy from municipal wastewater treatment in the Slo - metals) and biological contamination (thermo-tol - vak Republic is classified according to the Act no. erant coliform bacteria, faecal streptococci, and Mgr. Katarína Ondreičková, PhD. (*Corresponding author), Ing. Alžbeta Žofajová, PhD., Ing. Jozef Gubiš, PhD., Mgr. Martina Hudcovicová, PhD., National Agricultural and Food Centre – Research Institute of Plant Production, Bratislavská cesta 122, 921 68 Piešťany, Slovak Republic. E-mail: email@example.com Mgr. Michaela Piliarová, University of SS. Cyril and Methodius in Trnava, Nám. J. Herdu 2, 917 01 Trnava, Slovak Republic 52 Agriculture (Poľnohospodárstvo), 62, 2016 (2): 52−61 others). Simultaneously, concentrations of heavy practices have been described to have a direct effect metals may limit its acceptability for application to on the composition of bacterial community in the agricultural land. For these reasons, in Europe, its rhizosphere of agricultural plants (Berg & Smalla direct application to agricultural soil is governed by 2009; Berg et al. 2014). Council Directive 86/278/EEC of 12 June 1986 on For this reason, the aim of this study was to the protection of the environment, particular of the monitor and evaluate changes in the bacterial ge - soil when sewage sludge is used in agriculture, and netic diversity of the rhizosphere of barley and in the Slovak Republic by Act no. 188/2003 Z. z. In wheat as a result of the impact of soil additive de - both these acts, inter alia, a table about the limits of rived from sewage sludge and agricultural byprod - concentration of hazardous substances (heavy met - ucts represented by wastes from grain mill industry als) in sewage sludge is mentioned. Also, the acts and crushed corn cobs. Whereas via cultivation only set rules on how farmers can use sewage sludge as slightly to 1% of soil microorganisms can be detect - a fertiliser to prevent it from harming the environ - ed, to accomplish our goal, two culture-independent ment and human health by compromising the qual - methods were chosen – automated ribosomal inter - ity of the soil or surface and ground water ( http:// genic spacer analysis (ARISA) and terminal restric - eur-lex.europa.eu/legal-content/EN/TXT/?uri=cel- tion fragment length polymorphism (T-RFLP). Sub - ex%3A31986L0278). Only treated sludge may be sequently, an additional aim was the comparison of applied to agricultural soil, in which the concentra - these two molecular fingerprinting methods in order tion of hazardous substances does not exceed the to determine which is more suitable for the detec - limits in any of the monitored indicators, simulta- tion of bacterial genetic diversity. neously complies with microbiological criteria and has a minimum of 18% dry matter content. Maybe due to these strict criteria, application of sludge di - MATERIAL AND METHODS rectly to agricultural land in 2012 represented only 1.9% of the total amount of sludge produced in the Characteristics of soil additive and experimental Slovak Republic. design Sewage sludge is a rich source of organic matter, The sewage sludge used in all the experiments nutrients and trace elements, and can significantly was collected from the wastewater treatment plant improve the physico-chemical and biological soil Pannon-Víz Zrt. (Győr, Hungary) and was denot - properties. The basic condition for sewage sludge ed as concentrated, anaerobically digested, de - application in agriculture is that its use should not watered and dried. This sewage sludge was one cause soil and groundwater contamination. Nowa - part of the soil additive and agricultural by-prod - days, direct application of sewage sludge to soil is ucts, represented by wastes from grain mill in - generally considered one of the best ways of return - dustry and crushed corn cobs, another part (Top ing organic matter and nutrients to the soil. Direct Feed & Cargo Hungary Holding Zrt., Hungary). use of sewage sludge is linked to hygienic harmless - The final soil additive was prepared in the ratio ness in terms of content of hazardous elements and of 1:1.5 (sewage sludge : agricultural by-prod - pathogenic microorganisms. Application of treated ucts) using the low capacity granulator equip - sludge to the soil as a fertiliser benefits plants, but ment designed by Energy Agency Public Non - the effect of sludge addition on rhizosphere micro - profit Ltd. (Budapest, Hungary). The low capaci- organisms is less known. Generally, microorgan - ty granulator provided the mixing of both pri - isms in the rhizosphere play important roles in the mary composites and thermal treatment to ~ growth and ecological fitness of their plant host, and 75°C for inhibition of present microorganisms. the huge amount of organic carbon secreted by plant The elemental composition of the soil ad - roots forms, sustains and drives this rhizosphere ditive was: As – 6.5 ppm; Ca – 3.21%; Cd web (Buée et al. 2009). Different factors such as – ˂ 2 ppm; Cr – 67.5 ppm; Cu – 583 ppm; soil type, soil pH, plant species (cultivars), plant Fe – 3.13%; Mg – 0.21%; Mn – 0.03%; Ni – 44 ppm; developmental stage, or agricultural management Pb – 26 ppm; Sb – ˂ 2 ppm; Se – ˂ 1 ppm; Zn – 53 Agriculture (Poľnohospodárstvo), 62, 2016 (2): 52−61 1,510 ppm ( Šuňovská et al. 2013). For better char - removed from roots and the rhizosphere soil was acterisation of used sewage sludge and soil addi - scraped from roots with sterile scalpel, subsequently tive, see article by Šuňovská et al. (2013). cooled and stored before analysis at 4°C. This research was conducted at the Research Metagenomic DNA was extracted from the 300 mg TM Institute of Plant Production (RIPP), Piešťany. of fresh rhizosphere samples using the PowerSoil The pot experiment (5 kg of arable land/pot) was DNA Isolation kit (MoBio Laboratories, Inc., Carls - established by randomised complete block de - bad, USA) according to the manufacturer’s proto - sign in three replications using two agricultural col, but the extracted DNA was dissolved in 50 µl plants: spring barley, cultivar Levan and spring of nuclease-free water. The quantity and purity of wheat, line PS-6. Control samples represent - DNA was detected by NanoDrop-1000 Spectro - ed rhizosphere from pots without the addition photometer (Thermo Scientific, USA), and sam - of soil additive. Sludge samples represented rhi - ples were diluted to the same final concentration zosphere from pots with the addition of 15 t/ha (20 ng/µl). DNA was stored at ‒20 °C before use. of soil additive. Both plants were planted in the DNA was isolated immediately after sampling but pots with arable land from the field of RIPP Piešťa - the subsequent ARISA and T-RFLP analyses were ny (for characterisation of used land see article by conducted with all samples at once. Ondreičková et al. 2014), and the seeding rate was Automated ribosomal intergenic spacer analysis 10 seeds per pot (Figure 1). The ITSF/ITSReub (Cardinale et al. 2004) prim- Rhizosphere sampling and DNA isolation er set with 6-FAM fluorescent dye on the 5´ end of The samples were collected from the rhizo - the reverse primer was used for amplification of the sphere of barley and wheat in two stages – flower - 16S-23S rRNA intergenic transcribed spacer region ing – 10.5.2 stage by Feekes (June 2014) and plant from the bacterial rRNA operon. DNA amplification maturity – stage 11.4 by Feekes (July 2014) (Large was carried out in 50 µl reaction mixture containing 1954). Each sample was taken individually from 1 × PCR buffer (Invitrogen, Thermo Fisher Scientif - 2+ separate pots – 3 pots/3 individual controls, 3 pots/3 ic Inc., Waltham, USA), 1.5 mmol Mg , 0.25 μmol individual sludge samples. These three replicates of of both primers, 200 μmol of each dNTP (Invitro - the samples were collected as follows: plants were gen, Thermo Fisher Scientific Inc., Waltham, USA), taken out from soil, the soil residues were gently 1 U Taq DNA polymerase (Invitrogen, Thermo Fish - Figure 1. The pot experiment with addition of 15 t/ha of soil additive derived from sewage sludge and agricultural byproducts represented by wastes from grain mill industry and crushed corn cobs. (A) spring barley, cultivar Levan; (B) spring wheat, line PS-6. 54 Agriculture (Poľnohospodárstvo), 62, 2016 (2): 52−61 er Scientific Inc., Waltham, USA), and 1 μL (20 ng) abundance of phylotypes. The Gini-Simpson index of DNA extracted from the rhizosphere. The PCR (Jost 2006) was calculated as follows: 1 – λ = Ʃ(p ), was performed in a GeneAmp PCR System 9700 where λ is Simpson diversity index and p is the (Applied Biosystems, Thermo Fisher Scientific, proportion of an individual peak height relative to Inc., USA) using the following conditions: initial the sum of all peak heights. The Shannon’s diver - heat denaturation at 94°C for 3 min, followed by sity index (Shannon & Waever 1948) was calculat - 35 cycles each consisting of a denaturation step at ed as follows: H´ = – Ʃ(p ) (ln p ) and this index is i i 94°C for 45 s, annealing at 60°C for 1 min, exten - commonly used to characterize species diversity in sion at 72°C for 2 min and a final extension step at a community. Pielou evenness index (Pielou 1966) 72°C for 7 min. PCR amplification was confirmed was derived from Shannon’s diversity index and was by horizontal electrophoresis on a 1% (w/v) agarose calculated as follows: J´ = H´/ H´ , where H´ = max max gel in 1 × TBE buffer (1.1% (w/v) Tris-HCl; 0.1% ln(S) where S represents the total number of spe - (w/v) Na EDTA 2H O; 0.55% (w/v) boric acid), cies. Diversity indices were calculated using Excel 2 2 pre-stained with 0.10 µl/ml of ethidium bromide 2013. Cluster analysis was conducted using the bi - and visualised using ultraviolet illumination. PCR nary system – operational taxonomic unit (OTU) products were purified by the PCR Purification & and terminal restriction fragment (T-RF) peaks were Agarose Gel Extraction Combo kit (Ecoli s.r.o., Slo - classified as present (1) or absent (0) in each sample. vakia) and dissolved with 10 µl of sterile water. One The unweighed pair group method of cluster analy - microlitre of purified product was added to 9 µl for - sis using arithmetic means was used for grouping mamide containing LIZ1200 size standard (Applied of genotypes. Dendrograms were constructed based Biosystems, Thermo Fisher Scientific, Inc., USA), on Jaccard´s similarity coefficient using DARwin denatured at 95°C for 3 min and separated by cap - 5.0.158 statistical software (http://darwin.cirad.fr/ illary electrophoresis using ABI 3100 Prism Avant darwin; Perrier & Jacquemoud-Collet 2006). (Applied Biosystems, Thermo Fisher Scientific, Inc., USA). The electropherograms were analysed by Peak Scanner 2 (Applied Biosystems, USA). RESULTS AND DISCUSSION Only fragments within the range 200–1002 bp were used for evaluation with minimum peak height Total microbial biomass threshold of 50 fluorescence units. Metagenomic DNA extracted from the rhizo - sphere samples was used as a measure of microbi - Terminal restriction fragment length polymorphism al biomass (Figure 2). Microbial biomass, except This analysis was realised according to Ondre - during maturity stage in barley rhizosphere, was ickova and Kraic (2015), but purified PCR products higher in soils with soil additive. Interestingly, the were digested with MspI restriction enzyme (Prome - highest and also the lowest microbial biomass were ga Corp., Madison, USA) and terminal-restriction detected during maturity stage in wheat and bar - fragments (T-RFs) between 62 bp and 662 bp were used for evaluation. Only peaks above the threshold of 50 fluorescence units were considered. Statistical analyses Statistical significant differences among samples were tested by using the Fisher’s least significant difference (LSD) procedure at the 95.0% confidence level. LSD was performed using the software Stat - graphics X64 (Statpoint Technologies, Inc., Warren - ton, USA). Diversity indices were calculated from Figure 2. Total microbial biomass expressed as a standardized profiles of individual soil samples by metagenomic DNA extracted from the rhizosphere of barley and wheat from soil without and with addition of using the number and height of peaks in each pro - soil additive at a concentration of 15 t/ha. Bar represents file as representations of the number and relative standard deviation (n = 3). 55 Agriculture (Poľnohospodárstvo), 62, 2016 (2): 52−61 ley rhizosphere, respectively. At the same time, the dex, which is logical because of the huge number of highest difference in measured microbial biomass used sequences. The Shannon diversity index, with between control and sludge samples was detected in 20,000 sequences, showed that the untreated (con - wheat during the maturity stage; nevertheless, sta - trol) soil had the index value of 7.09 and the sludge tistically significant differences between control and soil had the value of 7.16. They also observed that sludge samples were not detected in any case ( LSD, the analysis using all detected sequences, showed α = 0.05). a positive correlation between the number of se - quences and Hʹ. Evenness index compares the simi - Bacterial genetic diversity larity of the population size of each species present Biological diversity can be quantified in many (Mulder et al. 2004). Unlike previous diversity in - different ways. One possibility is to measure the dices, no statistical differences between control and richness, in our case bacterial richness, which corre - sludge samples were detected by using Pielou even - sponds to the number of different species represent - ness index (Figure 3d). Overall, Figure 3 shows that ed in each rhizosphere samples. From Figure 3a, it the heights of each column (no values) are similar can be observed that richness value (No. of OTUs/ across all diversity indices. T-RFs) varies between control and sludge samples, but a statistically significant difference between Impact of sewage sludge on the composition of rhi- them was detected only in one case, during the zosphere bacterial communities flowering stage in wheat rhizosphere using T-RFLP To study the impact of soil additive derived analysis (Figure 3a). On the other hand, diversity from sewage sludge and agricultural byproducts indices provided more information about commu - represented by wastes from grain mill industry and nity composition than simply species richness. The crushed corn cobs on the composition of bacterial Gini-Simpson index equals the probability that the community in the barley and wheat rhizosphere, the two entities taken at random from the dataset of samples were statistically processed using cluster interest represent different types (Jost 2006). The analysis. In T-RFLP analysis, three samples for un - differences in measured values of this index using foreseen problems in capillary electrophoresis did ARISA between control and sludge samples were not give any product, i.e. one sample from barley, slight. But it is surprising that statistical difference one sample from wheat rhizosphere in flowering was detected at very similar values of control and stage with 15 t/ha of soil additive and one sample sludge samples, i.e. barley rhizosphere in maturity from wheat rhizosphere in maturity stage with 15 t/ha stage (Figure 3b). T-RFLP analysis yielded higher of soil additive. For this reason, these three samples differences between control and sludge samples, were not included in subsequent statistical evalua - and statistically significant difference was detected tion. also only in one case, in wheat rhizosphere during Cluster analysis was constructed using binary flowering stage (Figure 3b). Shannon’s diversity in - data and fluorescence intensity was not taken into dex, like the above-mentioned index, accounts for account. Dendrograms constructed from ARISA both abundance and evenness of the species present and T-RFLP data showed essentially similar results (Shannon & Waever 1948). Also, the Shannon index (Figure 4). The impact of the growth stage of barley (Hʹ) increases as both the richness and the evenness and wheat on the composition of bacterial commu - of the community increase, and high values of Hʹ nity is noticeable in both dendrograms. Bacterial would be representative of more diverse communi - communities in control samples from rhizosphere ties (Magurran 2004). Higher index values were ob - of both plants in flowering were very similar. These tained with the ARISA analysis than using T-RFLP, controls are located at the top (ARISA, Figure 4a) as well as these values were more balanced between or the bottom (T-RFLP, Figure 4b) of the dendro - the control and sludge samples. In both methods, grams. Samples collected from rhizosphere of ma - one statistical difference was detected between the ture plants were more dispersed within the whole said samples (Figure 3c). Poulsen et al. (2013) by dendrograms. It was probably due to the fact that, using pyrosequencing detected higher Shannon in - during the maturity stage, the plants were dry and 56 Agriculture (Poľnohospodárstvo), 62, 2016 (2): 52−61 a) b) c) d) Figure 3. Diversity indices and evenness detected in barley and wheat rhizosphere from soil without and with addition of soil additive at a concentration of 15 t/ha. Bar represents standard deviation (n = 3). *denotes statistically significant difference ( LSD, α = 0.05). Abbreviations: ARISA – automated ribosomal intergenic spacer analysis; LSD – least significant difference; T-RFLP – terminal restriction fragment length polymorphism 57 Agriculture (Poľnohospodárstvo), 62, 2016 (2): 52−61 their roots showed no or very low metabolic activi - main drivers that may cause the changes in microbi - ty. Therefore, this metabolic inactivity could result al community composition (Acosta-Martínez et al. in overgrowth of various types of bacteria, indepen - 2008; Lauber et al. 2008; Drenovsky et al. 2010), dent of root exudates secreted by barley or wheat. and likewise, the particle size fractions are more im - It is known that microbial population and mainly portant than the type of fertiliser applied (Sessitsch their activity in soil is significantly influenced by et al. 2001). That statement was supported by the plant roots (Bais et al. 2006). Furthermore, the plant results of MacDonald et al. (2011). They studied growth stage may be an important factor that shapes the impact of metal-rich sludge additions at sev - the composition of bacterial community in the rhizo - en experimental sites (five were under arable and sphere (Herschkovitz et al. 2005; Lerner et al. 2006) two under grassland management) and detected the because production and dispersion of root exudates strong effect of site on microbial community struc - are also affected by plant development (Hamlen et ture. Also, the metal effects were weak compared al. 1972). These exudates create a selective micro - to the effect of different site. Another approach has bial stimulation (Miller et al. 1989), which varies been used by Poulsen et al. (2013). They studied in function of time due to the plant age (Cavaglieri the impact of different urban waste and reference et al. 2009). In the dendrograms, the partial separa - fertilisers on prokaryotic diversity at one field site tion of soil samples with the addition of soil additive and found only small changes in the community from the control samples is also visible. Neverthe - composition due to different fertiliser treatments. less, this separation is not very significant and the Similarly, Nakatani et al. (2011) published that two impact of sewage sludge as a soil additive on the sequential annual applications of tannery sludge to bacterial composition in the barley and wheat rhizo - agricultural soils did not have negative impacts on sphere cannot be clearly confirmed. the microbial properties evaluated but denaturing The impact of sewage sludge on the composition gradient gel electrophoresis showed different pro - of bacterial community was not significant in this files at different sampling times. This was probably study. This is most likely due to the fact that, in our due to a rearrangement of bacterial communities in case, it was a pot experiment, using the same soil different treatments as a result of the exhaustion of type. It is known that land use and soil type are the easily degradable substrates towards the end of each a) b) Figure 4. Cluster analysis constructed from a) ARISA binary data and b) T-RFLP binary data of bacterial communities from barley and wheat rhizosphere from soil without and with addition of soil additive at a concentration of 15 t/ha. 58 Agriculture (Poľnohospodárstvo), 62, 2016 (2): 52−61 cycle of tannery sludge application. There are many ditive were not taken into account. As a result of studies with different results about the impact of using the hypervariable intergenic spacer, it is un - sludge on the soil microbial composition but some derstandable that the number of OTUs were statis - of the differences between the studies may be due to tically higher in ARISA than in T-RFLP. However, the use of different methods and also primers, which the range between the smallest and the largest num - have different biases (Poulsen et al. 2013). Mattana ber of OTUs was approximately the same in both et al. (2014) in their study of three sewage sludge methods (Figure 5a). For other diversity indices, the fractions (fresh, composted and thermally dried) range between the lowest and the highest value was and its impact on soil microbial community recom - lower in ARISA than in T-RFLP, which indicates mended that composting rather thermal drying can that the ARISA method yielded less variable values represent a more appropriate post-digestion process or, in other words, more consistent results. This is to make sewage sludge suitable for use as soil con - surprising in view of the fact that in T-RFLP, the ditioner in agriculture. conserved gene region is used, where we assumed more consistent results. The differences in the val - Mutual comparison of ARISA and T-RFLP ues of diversity indices between the two methods ARISA and T-RFLP belong to the molecular fin - were statistically significant ( LSD, α = 0.05). gerprinting methods and, in principle, are very simi - lar. The main difference is in the DNA region, which is used for PCR amplification – functional gene CONCLUSIONS in T-RFLP or highly variable intergenic spacer in ARISA. This determines the subsequent steps in Our pot experiment with the addition of soil ad - these methods. Results obtained from both methods ditive derived from sewage sludge and agricultural about diversity indices were statistically significant byproducts, represented by wastes from grain mill (Figure 5). In this statistical evaluation, plant spe - industry and crushed corn cobs, to arable land at cies, plant growth stages and addition of soil ad - the rate 15 t/ha did not reveal differences between a) b) c) d) Figure 5. The comparison of ARISA and T-RFLP methods using Box and Whisker plots that were created using data from diversity indices and evenness. *denotes statistically significant difference ( LSD, α = 0.05). Abbreviations: ARISA – automated ribosomal intergenic spacer analysis; LSD – least significant difference; T-RFLP – terminal restriction fragment length polymorphism 59 Agriculture (Poľnohospodárstvo), 62, 2016 (2): 52−61 and fungi, and of some of their structuring factors. control and samples with sludge in the composition In Plant Soil , vol. 321 , pp. 189–212. DOI 10.1007/ of bacterial community in barley and wheat rhizo - s11104-009-9991-3 sphere. Only minor temporal changes in the com - CARDINALE, M. – BRUSETTI, L. – QUATRINI, P. – position of bacterial community between flowering BORIN, S. – PUGLIA, A.M. – RIZZI, A. – ZANAR - DINI, E. – SORLINI, C. – CORSELLI, C. – DAF - and maturity periods were observed. These chang - FONCHIO, D. 2004. Comparison of different primer es were related to the samples collected during sets for use in automated ribosomal intergenic spacer the plant maturity stage. Whereas the plants were analysis of complex bacterial communities. 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