Introduction
Soil microorganisms interact with plants in various ways, influencing their health and productivity. Plants commonly produce root exudates or other easily degraded chemicals to induce the formation of a rhizosphere microbial community structure [2]. Soil microorganisms are involved in controlling C and N cycles, providing nutrients to the plant, and playing an important role in the fertility and structure of the soil [16]. Rhizosphere soil has a ten times greater biota population compared with bulk soil, and the interaction between the plant and microorganisms within the rhizosphere is an important factor in sustainable agriculture [3].
Because of the importance of how soil microorganisms affect plants, studies have been carried out on how genetically modified (GM) crops influence the soil microbial community since the commercialization of GM crops in 1996. The cultivation of GM crops has raised concerns regarding horizontal gene transfer of the introduced gene in the GM plants to soil microorganisms as well as the effect on non-target organisms within the soil microbial community [29]. GM crops can affect the soil microbial community in both direct and indirect ways [19]. Direct effects include the action spectrum of the protein produced by the transgene and the amount of protein accumulated within the environment. The indirect effects include changes in plant proteins and root exudates as a result of the changes in the metabolic pathway of the plant due to the transformed gene. The indirect effects on soil microbial communities are more difficult to analyze compared with the direct effects because various elements can affect the formation of root exudates and the resulting soil microbial community structure. Therefore, the indirect effects on soil microbial communities cannot be analyzed through a simple assay alone, but must be analyzed comprehensively using several assays. GM crops have been found to have no effect, a minor effect, or a statistically significant effect compared with the original cultivars on the soil microbial community. These results have been obtained through both cultivation methods and molecular techniques [13]. Recently, many studies have adopted a systematic investigative approach using a next-generation sequencing technique, such as pyrosequencing to overcome the limited capabilities of previous ecological techniques.
The CaMSRB2 gene has been isolated from pepper and reported to induce resistance against oxidative stress caused by reactive oxygen species (ROS) [15]. When the plant experiences biotic or abiotic stresses, ROS are produced, which oxidize the sulfur bonds of methionine and cysteine, inducing changes in proteins. There are two forms of methionine sulfide, the R-form and the S-form, which can be reduced back to methionine by two proteins: methionine sulfoxide reductase A (MsrA) and MsrB [9]. These proteins exist in all organisms, including microorganisms, and have been proven to be an important enzyme from an evolutionary perspective. Studies of yeasts that overexpress the MsrA or MsrB gene or have mutant version of one of these genes have shown that the enzymes produced by these genes play a protective role against oxidative stress [23]. Additionally, under oxidative stress condition, mice with mutant MsrA has been found to have a 40% reduced life span compared with control mice [21]. Transgenic rice that expresses the CaMSRB2 gene has been found to have increased resistance against pathogens, which has sparked interest in the study of this gene not only in biotic, but also abiotic stress conditions such as cold and drought where ROS are produced [15]. Compared with other cereal crops such as maize and wheat, rice is sensitive to decreases in soil water content because rice cultivars have been historically grown under flood irrigation conditions where the soil matric potential is zero [27]. Large amounts of water are required for production of rice compared with other crops. Drought-tolerant rice is of great importance in the world today where climate change has raised concerns regarding food production. Kim et al. [15] reported that the transgenic rice MSRB2-Bar-8, which expresses the CaMSRB2 gene, induces drought tolerance through the protection of chloroplast-targeted genes. However, an evaluation of the environmental risks of drought-tolerant transgenic rice and how it affects soil microorganisms must be undertaken before the commercialized cultivation of this crop.
This is a preliminary study on the effects of cultivating transgenic rice MSRB2-Bar-8, transformed with the CaMSRB2 gene, on the soil microbial community compared with the effects on the soil microorganisms by the parental rice cultivar, Ilmi. We carried out the following analyses at different stages of rice growth: (i) chemical analyses of the soil, (ii) population density analyses of the microbial communities, and (iii) pyrosequencing analysis of the microbial communities to determine the differences in community structure.
Materials and Methods
Site and Sampling
The experimental plot for MSRB2-Bar-8 and Ilmi rice cultivation was constructed in an isolated GMO experimental field at the National Academy of Agricultural Science (NAAS), Rural Development Administration located in Suwon, Korea. MSRB2-Bar-8 and Ilmi seeds were sown in a seedling box and then transplanted in June 2012, after 3 weeks, to three 4 × 4 m fields. Three replicates of rhizosphere soil samples were collected from each of the fields during the seedling, tillering, and maturity stages. Samples were taken from tightly root-associated soils, removing the bulk soil surrounding the rice roots.
Soil Chemical Analyses
After collection, the soil samples were dried and then passed through a 2 mm sieve for chemical analyses. These analysis were done according to the methods described by the NAAS [22]. The pH was measured with a pH meter, with the soil suspension produced by mixing soil and distilled water to a ratio of 1:5. Total nitrogen and carbon composition were obtained via an elemental analyzer (Vario Max CN; Elementar, Germany). Available phosphate was measured using the Lancaster method using a calorimetry assay. Exchangeable cations such as calcium, potassium, magnesium, and sodium were diffused by 1N ammonium acetate (pH 7.0) and then analyzed using ICP (GBC Integra XL, Australia).
Microbial Density Analysis
The density of soil microbes was assessed by enumeration of cultured total bacteria and fungi after inoculating soil samples in each selective medium. Ten grams of fresh soil was immersed in 90 ml of sterilized 0.85% NaCl solution and then suspended for 30 min using a shaking incubator (Vision Co., Korea) at 200 rpm. A series of dilutions were made using the suspension, and these dilutions were smeared onto three Petri dishes with R2A agar (Difco, Detroit, USA) containing cycloheximide (0.05 g/l) for bacterial culture, and three Petri dishes with R2A agar containing chloramphenicol (0.02%) for fungal culture. The bacteria and fungi inoculated media were incubated at 28℃ for 2 and 4 days, respectively, prior to counting the number of colonies. The number of microorganisms for each sample was calculated by counting the number of colonies in each of the three Petri dishes and using the average value as the colony forming unit (CFU/g dry soil).
Pyrosequencing Analysis
Metagenomic DNA was extracted from microorganisms in the soil using a FastDNA Spin Kit (MP Biomedicals, USA) according to the manufacturer’s manual. The extracted DNA was used for pyrosequencing analysis as reported by Hur et al. [12]. PCR amplifications were performed using a C1000 Touch Thermal Cycler (Bio-Rad, CA, USA) and barcoded fusion primers (http://www.ezbiocloud.net/resource/M1001). A total of 100 ng of template DNA was added to the PCR (total volume of 50 μl), which contained Ex Taq buffer, 0.2 mM of each dNTP, 0.5 μM of each primer, and 2 units of Ex Taq (Takara, Otsu, Japan). After initial denaturation (94℃ for 5 min), the PCR was carried out using the touchdown program to undergo 10 cycles of denaturation (94℃ for 30 sec), annealing (60℃ for 45 sec), and extension (72℃ for 90 sec), where the annealing temperature was decreased by 0.5℃ for each subsequent cycle. A further 20 cycles of denaturation (94℃ for 30 sec), annealing (55℃ for 45 sec), and extension (72℃ for 90 sec) were carried out. The amplified products were confirmed by 2% agarose gel electrophoresis and visualized using the Gel Doc system (Bio-Rad). Amplicons were purified using a QIAquick PCR Purification Kit (Qiagen, CA, USA) and quantified using a PicoGreen dsDNA Assay Kit (Invitrogen, CA, USA). Equimolar concentrations of each amplicon from the different samples were pooled and purified using an AMPure bead kit (Agencourt Bioscience, MA, USA) and then amplified on sequencing beads with emulsion PCR. Sequencing reactions were performed using a Roche GS FLX Titanium System at ChunLab Inc. (Seoul, Korea) according to the manufacturer’s instructions.
Pyrosequence Data Analysis
The obtained sequences were compared and classified using the EzTaxon Database (http://www.ezbiocloud.net). A rarefaction curve that shows the increase in the ratio of operational taxonomic units (OTUs) to the analyzed sequence number was constructed based on the CD-HIT and Mothur software packages [25]. The number of OTUs was calculated from the sequence group that showed 97% sequence homology based on the taxonomy-based clustering de novo clustering algorithm [17], and this number was used to calculate the Shannon diversity index (H), which is a measure of diversity and evenness, and the richness estimators ACE and Chao 1. To compare OTUs between samples, shared OTUs were obtained with a taxon exclusive or (XOR) analysis using the CLcommunity program (ChunLab, Seoul, Korea) according to Khodakovskaya et al. [14]. For this analysis, the number of reads for all soil samples was normalized using the program prior to carrying out XOR analysis at the phylum, class, order, family, genus, and species levels. PermutMatrix software [4] was used to generate a heat map of bacterial diversity by hierarchical clustering using the Manhattan distance method with no scaling and an unweighted-pair technique. The similarity between each pair of communities was estimated using the Fast UniFrac web interface [11] and visualized using the unweighted pair group method with arithmetic mean (UPGMA) dendrogram.
Results and Discussion
Chemical Characteristics of Soil Samples
Because a difference in the soil chemical composition can affect soil microbial communities, the soil pH, available phosphate, electrical conductivity, cations, total nitrogen, and organic matter were analyzed to compare the difference in the rhizosphere soil of MSRB2-Bar-8 versus Ilmi rice (Table S1). There was no significant difference in soil pH between MSRB2-Bar-8 (pH 6.1–6.3) and Ilmi rice (pH 6.2–6.5). pH is known to have an important effect on soil microbial community structure and biogeochemical function [10,24] as it can cause changes in nutrient availability, especially C, N, and P, and have a strong effect on plant composition and productivity [7]. In this study, the available phosphate was 75.6–98.9 mg/kg for MSRB2-Bar-8 and 72.7–97.7 mg/kg for Ilmi rice soil, showing no significant difference between the two. The soil electrical conductivity for both MSRB2-Bar-8 and Ilmi rice was found to be 0.2–0.3 dS/m, and the total nitrogen content was similar. Moreover, there were no significant differences in either organic matter or cations such as K+, Ca2+, Mg2+, or Na+ between MSRB2-Bar-8 and Ilmi rice soils. Changes in the microbial community structure by environmental factors such as temperature, humidity, oxygen availability, and pH can ultimately lead to a change in soil enzyme activity that decomposes organic matter [8,26,28]. The overall analysis of these chemical factors showed no significant differences between the soils of GM and non-GM plants. The results indicate that if any differences are found in the soil microbial structure between GM soil and non-GM plants, it will be a result of the cultivation of the GM crop.
Density Analysis of Soil Microbial Communities
Significant differences in bacterial population density were found in the different growth stages of rice, whereas none were found in the fungi populations except the seedling stage (Table S2). Changes in the production of root exudates over different plant growth stages can cause changes in the microbial community structure inhabiting the rhizosphere. In Arabidopsis, the production of secreted root exudates differs according to growth stage, where in the early stages the plant produces relatively more sugar and sugar alcohols, while at later growth stages, amino acids and phenolic acids are produced relatively more [5,6]. This difference in exudates at different growth stages is suspected to be due to the plant secreting sugars for various nonspecific microorganisms in the early growth stages, but secreting specific substrates and latent antimicrobial compounds to the rhizosphere to select for particular microbial inhabitants as the plant ages. Another example of plant root exudates changing over time is explained by a plant’s tendency to require more nitrogen throughout its growth stages, yet it is currently unknown how the plant obtains this nitrogen under natural conditions. It has been demonstrated that symbiotic relationships between soybeans and rhizobacteria only occur under nitrogen-limited conditions. Plants secrete flavones and flavonols under nitrogen-deficient conditions to initiate the symbiotic relationship between root nodules and rhizobacteria, which indicates the plant can partially control the identity and functionality of the soil microorganisms [20,30,31]. Therefore, a change in even a single metabolite secreted by the plant can induce a change in the microbial community. As such, it is important to carry out detailed analyses of GM crops with transformed genes that produce proteins that are exuded to the rhizosphere soil microorganisms. In the present study, the results of such an analysis showed that there were differences in the density of microorganisms between growth stages, but no significant differences were found between the soils of GM and non-GM crops.
Bacterial Community Structure Analysis Using Pyrosequencing
The total number of pyrosequence reads for the Ilmi and MSRB2-Bar-8 soils were 26,991 and 26,293, respectively. Analysis of the rarefaction curve for both soils showed neither had reached the saturation point (data not shown). There were no significant differences in diversity except for the Ilmi soil from the maturity stage. However, richness was significantly higher in the soils of MSRB2-Bar-8, collected on June, August, and October, compared with Ilmi soils collected during the same periods (Table 1). These results also correlated with the rarefaction curve analysis results (data not shown).
Table 1.Estimates of the Shannon index were obtained based on 3% differences in DNA sequence alignments. IM, Ilmi; MSRB2-Bar-8, CaMSRB2-expressing transgenic rice line 8.
The range of the number of pyrosequence reads differed in each soil sample; thus, a standardization of the number of reads was carried out according to Schloss et al. [25] to obtain an unbiased estimate of diversity and to analyze the microbial community structure for the soils collected at different time periods. Analysis of the normalized sequence dataset resulted in 11 phyla that had over 1% distribution percentage in the seedling-stage soil (Fig. 1A). Proteobacteria and Chloroflexi were found to be the most abundant in both the Ilmi and MSRB2-Bar-8 soil microbial communities. The next most frequent phyla in the two soils were Firmicutes, Actinobacteria, and Acidobacteria. The remaining phyla represented included Nitrospirae, Bacteroidetes, Planctomycetes, Chlorobi, Gemmatimonadetes, and Cyanobacteria. Proteobacteria and Chloroflexi were also most abundant in tillering soils, with other phyla present, including Nitrospirae, Bacteroidetes, Gemmatimonadetes, Chlorobi, Planctomycetes, and Cyanobacteria (Fig. 1B). The maturity-stage soil likewise contained Proteobacteria and Chloroflexi in the highest abundances, but Chloroflexi was found to be relatively higher than in the previous two stages (Fig. 1C). Phyla present in lower abundances included Bacteroidetes, Nitrospirae, Chlorobi, Gemmatimonadetes, Planctomycetes, and Cyanobacteria. At the class level, Anaerolineae and Alphaproteobacteria were the most abundant in the seedling stage, while Anaerolineae and Deltaproteobacteria were the most abundant for the other stages (Table 2). In the case of Anaerolineae, this class was found to be increasingly more abundant (in relative measure) compared with the other stages. The classes present in lower abundances included Gemmatimonadetes_c, Nitrospira_c, Rubrobacteria, Chloracidobacterium_c, Dehalococcoidetes, Acidimicrobiia, and Planctomycetacia. A comparative analysis of the degree of microorganism diversity between soils of different time periods at a family level using a heat map showed Anaerolinaceae and Geobacteraceae increasing in abundance, while Bradyrhizobiaceae, Clostridiaceae, and Bacillaceae decreased in abundance throughout the maturity stage (Fig. 2).
Fig. 1.Comparison of the bacterial composition in non-GM (Ilmi) and GM (MSRB2-Bar-8) rhizosphere soils. (A) Seedling stage; (B) Tillering stage; (C) Maturity stage. IM, Ilmi; MSRB2-Bar-8, CaMSRB2-expressing transgenic rice line 8: OTU, operational taxonomic unit.
Table 2.The total number of sequences is presented after normalizing for sample size. IM, Ilmi; MSRB2-Bar-8, CaMSRB2-expressing transgenic rice line 8.
Fig. 2.Heat map depicting bacterial diversity between GM (MSRB2-Bar-8) and non-GM (Ilmi) rice soils during different growth stages (seedling, tillering, and maturity). The hierarchical dendrogram shows the composition and distribution of families and classes. Clustering in the Y-direction indicates divergence in abundance, not phylogenetic similarity. The scale defines the relative abundance of the phylogenetic groups as depicted by the colors in the heat map.
A comparative analysis of the unique microorganisms by phylogenetic rank for GM and non-GM soils over different growth stages showed differences in the microbial phyla (Table 3). At the phylum level, there were 7~22 phyla unique to each soil, 27~47 classes at a class level, 68~112 at a order level, 195~237 at a family level, 420~533 at a genus level, and 779~1,089 at a species level. Differences in the microbial community structure between the Ilmi and MSRB2-Bar-8 soils are suspected to be from unintentional changes in composition of root exudates or the direct effects of transgenic proteins on soil microorganisms; however, owing to the limited knowledge about the correlation between microbial community structure and function, more study needs to be done for further evaluation of the effects of MSRB2-Bar-8 on soil microorganisms. UPGMA dendrogram analysis examining overall similarity between the two soil bacterial communities showed that the soils grouped by time period (Fig. 3). The GM and non-GM soils were more similar at the tillering and maturity stages compared with the seedling stages. In a study by Arjun and Harikrishnan [1], the major phylum found in the rice rhizosphere soil was Proteobacteria, and the minor phyla contained Acidobacteria, Firmicutes, and Bacteroidetes, which is similar to the current study’s results for the MSRB2-Bar-8 soil. In the present study, analysis of rice rhizosphere soil microorganisms was subdivided according to growth stage, which showed a difference in the densities of the major phyla of microorganisms. Although the mechanism was different, analysis of the community structure of soil microorganisms of another drought-resistant transgenic rice, ABC-TPSP, similarly demonstrated no significant differences between the GM and non-GM soils in terms of the diversity index according to the ribotype number [18]. It was shown that the cultivation of ABC-TPSP rice did not affect the bacterial and fungal community structure.
Table 3.aThe number of taxa present in Ilmi rhizosphere soil but not in MSRB2-Bar-8 soil. IM, Ilmi; MSRB2-Bar-8, CaMSRB2-expressing transgenic rice line 8.
Fig. 3.Unweighted pair group method with arithmetic mean dendrogram analysis of 16S rRNA genes in non-GM (Ilmi; IM) and GM (MSRB2-Bar-8) rice soil samples based on Bray-Curtis dissimilarities of total bacteria. (S), Rhizosphere soil collected at the seedling stage; (T), Rhizosphere soil collected at the tillering stage; (M), Rhizosphere soil collected at the maturity stage.
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