Nitrogen-transforming archaea and bacteria in tropical soils are affected under transgenic as ...

33 Pages·2014·0.98 MB·Spanish

AEM Accepts, published online ahead of print on 8 August 2014
Appl. Environ. Microbiol. doi:10.1128/AEM.01778-14
Copyright © 2014, American Society for Microbiology. All Rights Reserved.
1 Nitrogen-transforming archaea and bacteria in tropical soils are affected under
2 transgenic as compared to non-transgenic maize
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4 Simone Raposo Cotta1,4, Armando Cavalcante Franco Dias2,4, Ivanildo Evódio Marriel3,
5 Fernando Dini Andreote2, Lucy Seldin1* and Jan Dirk van Elsas4 D
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7 1 Universidade Federal do Rio de Janeiro, Instituto de Microbiologia Paulo de Góes, Rio ed

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8 de Janeiro, Brazil; o
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9 2 Departamento de Ciência do Solo, Escola Superior de Agricultura Luiz de Queiroz, tt
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10 Universidade de São Paulo, Piracicaba, São Paulo, Brazil; a
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11 3 EMBRAPA/CNPMS - Empresa Brasileira de Pesquisa Agropecuária, Centro Nacional .a
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12 de Pesquisas de Milho e Sorgo, Sete Lagoas, MG, Brazil; .
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13 4 Department of Microbial Ecology, Center for Ecological and Evolutionary Studies /
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14 (CEES), University of Groningen (RUG), Nijenborgh 7, 9747AG Groningen, The N
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15 Netherlands. m
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19 *Corresponding author: Lucy Seldin - E-mail ([email protected]), Laboratório de e
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20 Genética Microbiana, Instituto de Microbiologia Paulo de Góes, Universidade Federal
21 do Rio de Janeiro, Centro de Ciências da Saúde, Bloco I, Ilha do Fundão, Rio de
22 Janeiro, RJ, CEP 21941-590, Brazil.
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24 Abstract
25 The composition of the rhizosphere microbiome is a result of interactions between plant
26 roots, soil and environmental conditions. Within plant species, the impact of genetic
27 variation on the composition of the root-associated microbiota is as-yet poorly
28 understood. This study assessed the abundances and structures of nitrogen-transforming
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29 (ammonia-oxidizing) archaea and bacteria as well as nitrogen fixing bacteria as driven w
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30 by genetic modification of their maize host plants. The data show that significant a
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31 changes occurred in the abundances (revealed by qPCR) of ammonia-oxidizing bacterial
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32 and archaeal communities as a result of the maize host being genetically-modified. In

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33 contrast, the structures of the total communities (determined by PCR-DGGE) were p
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34 mainly driven by factors such as soil type and season, but not by plant genotype. Thus, e
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35 ammonia-oxidizing bacterial and archaeal community abundances, but not community s
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36 structures, revealed to be responsive to changes in maize genotype, allowing the r
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37 suggestion that they are explored to serve as candidate bioindicators for monitoring the on

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38 possible impacts of cultivation of GM plants. o
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40 Key words: Maize, GM plant, Ammonia oxidizers, nitrogen fixers 1
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48 INTRODUCTION
49 The relationship between plants and soil microbes is well established in the literature.
50 Several microbial types or consortia are supposed, or known, to be able to exert strong
51 effects on plant fitness (1, 2, 3). These relationships are often specific, suggesting that
52 changes in plant genotype can have an impact on the association of specific microbial
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53 groups with plants, thus altering the composition of the rhizosphere microbiome (2).
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54 Based on this premise, several authors suggested that genetic modifications of plants a
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55 may modulate rhizosphere biodiversity, and possibly impact on the functioning of the f
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56 rhizosphere (4, 5, 6). Therefore, microorganisms have been broadly used to determine

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57 the possible effects of GM plants on the soil environment. Some authors have indeed p:
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58 reported modifications in the structure, composition and abundance of particular (non- m
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59 target) microbial groups (6, 7). However, these effects were in general quite transient (6, s
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60 8, 9). r
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61 For the detection of relevant shifts in the soil microbiota, functional microbial n

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62 groups that are of low redundancy are prime candidates, as: i) their roles may be critical ov
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63 for the maintenance of soil functioning; ii) they may be more responsive to b
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64 environmental factors than high-redundancy groups. This counts for both natural and 1
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65 managed agricultural soils. Several functional microbial communities have been shown 0
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66 to be sensitive to changes in environmental parameters (10), for example, those b
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67 involved in transformations of nutrients like sulfur and/or nitrogen (11, 12, 13). u
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68 In terms of the nitrogen cycle, two processes may be forwarded as being
69 strongly modulated by environmental parameters, i.e. nitrification (14) and nitrogen
70 fixation (13). Nitrification occurs in two steps: the first and rate-limiting step is the
71 oxidation of ammonia to hydroxylamine, which is further oxidized to nitrite. The
72 second step, performed by nitrite-oxidizing bacteria, encompasses the oxidation of
73 nitrite to nitrate (15, 16). The oxidation of ammonia is catalyzed by the enzyme
74 ammonia monooxygenase, which is produced by a few (phylogenetically-restricted)
75 Proteobacteria (ammonia oxidizing bacteria - AOB) and some Archaea, belonging to the
76 phylum Thaumarcheaeota (ammonia oxidizing archaea - AOA) (14, 17, 18). Nitrogen
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77 fixation is the biological reduction of atmospheric nitrogen into ammonia, a step that is
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78 essentially performed by bacteria that harbor the nifH gene, a key gene coding for the a
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79 structural part of nitrogenase, nitrogenase reductase (19). f
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80 We hypothesized that the cultivation of GM instead of non-GM maize, as a

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81 result of the modification, would change the relationship between the plants and the p:
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82 targeted nitrogen-cycling organisms, causing modifications in the structure and m
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83 abundance of ammonia oxidizing and nitrogen fixing communities in the rhizosphere. s
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84 The objective of this work was thus to determine the possible differential assembly of r
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85 the selected functional microbial groups in the rhizosphere of the GM as compared to n

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86 the parental (conventional) maize in a field experiment. We used culture-independent ov
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87 analyses to perform this survey, as these provide the best-possible picture of the b
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88 targeted communities, basing our analyses on proxies for the amoA gene for nitrifiers 1
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89 (AOA and AOB) and the nifH gene for nitrogen fixers. 0
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91 MATERIAL AND METHODS u
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93 Maize cultivars and experimental conditions
94 An experimental field located at EMBRAPA Milho e Sorgo, in the city of Sete Lagoas,
95 State of Minas Gerais, Brazil, was used. A detailed description of the field was
96 described by Cotta et al. (20). Replicate plots of two different soils were used, one
97 typical for the Cerrado region in Brazil (dark-red acid distrophic latosol with a clayey
98 texture), and another commonly found in Varzea areas (low humus, eutrophic gley soil
99 with a clayey texture, sub-neutral pH). In these soils, two maize hybrids, both
100 expressing a Bacillus thuringiensis (Bt) insect toxin were used: i) MON810 genotype
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101 30F35Y (expressing the insecticidal Bt-toxin Cry1Ab), and ii) TC1507 genotype
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102 30F35H (expressing the insecticidal Bt-toxin Cry1F and the herbicide resistance a
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103 phosphinothricin-N-acetyltransferase [pat gene] from Streptomyces f
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104 viridochromogenes). The isogenic parental line of both GM maize cultivars was used as

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105 the control. p:
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106 Plants were cultivated during the traditional period for maize cultivation in m
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107 Brazil, known as “Safra” (second semester/harvest in August - rainy period of the year) s
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108 and also during a non-traditional period for maize cultivation, known as “Safrinha” r
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109 (first semester/harvest in February - dry period of the year). Sampling expeditions were n

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110 performed at three time points; during the transition from the vegetative to the ov
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111 reproductive stage of growth (30 days), at flowering (60 days) and during grain filling b
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112 and maturity (90 days). At each time point, three sets of three plants of each cultivar 1
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113 were harvested. Roots of these plants were shaken manually to remove the loosely- 0
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114 attached soil. The soil adhering to the roots of each set of three plants was then pooled, b
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115 homogenized and considered as one sample of the rhizosphere soil. This yielded three u
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116 replicates per treatment, and a total of 54 samples analyzed (3 periods x 3 treatments x 2
117 periods of cultivations x 3 replications). The samples were kept at -20ºC until DNA
118 extraction and further analyses.
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120 Determination of the rhizosphere pH, ammonium and nitrate concentrations
121 The chemical characteristics of rhizosphere samples were determined at EMBRAPA
122 Milho e Sorgo, where the pH was determined in water as described by Silva et al. (21).
123 Nitrate (NO3-) and ammonium (NH4+) contents were determined using a standard
124 protocol described by Keeney & Nelson (22).
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126 Extraction of DNA from rhizosphere samples a
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127 Total DNA from microbial communities was extracted directly from the rhizosphere f
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128 soil samples (0.5 g of each sample in triplicate) using the FastPrep Spin kit for soil

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129 DNA (BIO 101 Systems, USA). DNA preparations were visualized by electrophoresis p:
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130 in a 0.8% agarose gel in 1x TBE buffer (23) to assess yield and integrity. Samples were m
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131 then stored at -20oC prior to PCR amplifications. s
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132 r
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133 Quantification of AOA, AOB and diazotrophic communities by qPCR n

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134 The abundance of AOA, AOB and diazotrophic organisms was estimated by using, as ov
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135 proxies, the amoA gene from archaea and bacteria, and the nifH gene, respectively. b
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136 Quantifications were carried out twice from each of the soil samples using the ABI 1
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137 prism 7300 Cycler (Applied Biosystems, Germany) with SYBR Green I. The reactions 0
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138 were performed in 25µl reactions containing 12.5 µl of reaction mixture SensiMix b
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139 SYBR kit (Bioline Life Sciences, Germany), 0.2µM of specific primers for each gene, u
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140 0.2 µg of BSA (Bovine Serum Albumine), and 2 µl of target DNA (aprox. 10 ng).
141 Primers crenaamo23F (24) and crenamoA616R48x (25) were used to quantify AOA,
142 resulting in fragments of 624 bp. Thermal cycling consisted of 94oC for 5 min, followed
143 by 40 cycles of denaturation at 94oC for 45 s, primer annealing at 50oC for 45 s, and
144 elongation at 72oC for 45 s. Similarly, AOB quantification was performed using primers
145 amoA-1F and amoA-2R according to Nicol et al. (25). Amplifications were conducted
146 according to the following cycle parameters: initial denaturation step at 94oC for 10
147 min; 40 cycles at 94oC for 1 min, 60oC for 1 min and 72oC for 1 min. For the
148 quantification of the gene nifH the primers FGPH19 and PolR were used, as described
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149 by Taketani et al. (26). The amplification conditions were: an initial denaturation step at
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150 94oC for 10 min followed by 40 cycles of 1 min at 94oC; 27 s at 57oC; 1 min at 72oC. a
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151 The specificity of amplification products was confirmed by melting curve analysis, and f
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152 the sizes of the amplified fragments were checked in a 1.5% agarose gel stained with

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153 ethidium bromide. For quantification of target genes, standard curves were constructed p:
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154 by performing amplification with the known number of copies of template DNA, added m
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155 in serial dilutions in the reactions (107 to 102 copies to AOA, 108 to 101 copies to AOB s
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156 and 106 to 101 copies to nifH). The amplification efficiency was 100% for AOA, 109% or
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157 for AOB and 93.26% for nifH. The data from amplification of rhizosphere DNA (Ct) n

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158 was interpolated to determine the number of copies of the target genes the sample. ov
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159 Amplification of different amounts of target DNA (standard curve) also resulted in the b
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160 determination of amplification efficiency and logarithmic correlation (R2) between the 1
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161 number of cycles and the amount of DNA. 0
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163 PCR-DGGE analysis of the AOA, AOB and diazotrophic communities g
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164 The analysis of AOA was performed using 50 µl reactions containing 10 ng of genomic t
165 DNA and 0.2 mM of primers crenaamo23F and crenaamoA616R, 2.0 mM MgCl2, 250
166 nM dNTPs, 5U Taq polymerase in the buffer supplied by the manufacturer (Bioline Life
167 Science, Germany). Amplification conditions were as follows: initial denaturation step
168 at 95oC for 5 min; 10 cycles of 30 s at 94oC, 30 s at 55oC, 1 min at 72oC; 20 cycles of 30
169 s at 92oC, 30 s at 55oC, 1 min 72oC; and a final extension of 10 min at 72oC. As a
170 molecular marker for the AOB community, we used a region of the 16S rRNA gene,
171 specific for the AOB of the betaproteobacterial subdivision using forward primers CTO-
172 A/CTO-B/CTO-C and reverse primer CTO-R (27). The reactions were carried out using
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173 Bioline Taq polymerase (Bioline Life Science, Germany) using the manufacturer’s
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174 buffer. MgCl2 was added to a final concentration of 2.0 mM, nucleotides at 250 nM and ad
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175 bovine serum albumin (BSA) at 0.4 mg ml-1. Amplification conditions were as follows: f
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176 an initial denaturation step at 93oC for 1 min; 35 cycles of 30 s at 92oC, 1 min at 57oC,

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177 45 s at 68oC; a final extension of 5 min at 68oC. The resulting amplicons were used as p:
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178 templates in the second PCR reaction with bacterial primers GC-341F and 518R (28). In m
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179 this reaction, a 170-bp amplicon was generated. s
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180 As a molecular marker for the diazotrophic community, we used the nifH gene, r
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181 amplified in a nested PCR as described by Diallo et al. (29). For the first reaction, the n

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182 forward primer FPGH19 and reverse primer PolR were used at a final concentration of ov
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183 0.5 µM. The reaction was carried out using Roche Taq polymerase (Roche, Germany) b
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184 using the manufacturer’s buffer supplied with MgCl2. The dNTP was added to a final 18
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185 concentration of 200 nM and bovine serum albumin (BSA) at 0.4 mg ml-1 in 25 µl 20
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186 volumes. Amplification conditions were as follows: an initial denaturation step at 94oC b
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187 for 5 min; 30 cycles of 1 min at 94oC, 1 min at 56oC, 2 min 72oC; and a final extension u
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188 of 15 min at 72oC. The resulting amplicons were used as template in the second PCR t
189 reaction with forward primer PolF-GC clamp together with the reverse primer AQER.
190 In this reaction, a 360-bp amplicon was generated with the same PCR mix conditions
191 used in the first reaction. Amplification conditions were as follows: an initial
192 denaturation step at 94oC for 5 min; 30 cycles of 1 min at 94oC, 1 min at 48oC, 2 min
193 72oC; and a final extension of 15 min at 72oC.
194 All amplification systems were validated through cloning and sequencing as
195 described by Dias et al. (14). Briefly, amplicons obtained from each primer set were
196 cloned into the vector pGEM-T (Promega, Leiden, The Netherlands). Randomly
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197 selected clones were PCR amplified with relevant primers and sequenced at the
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198 facilities of the University of São Paulo, Brazil (USP: a
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199 http://genfis40.esalq.usp.br/multi/) using Sanger methodology. The resulting sequences f
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200 were compared to database sequences using BlastN (http://www.ncbi.nlm.nih.gov). The

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201 sequences obtained in this study were deposited in the GenBank database with the p:
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202 following accession number: AOA (KJ866487-KJ866491); AOB (KJ866492- m
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203 KJ866496); nifH (KJ866497-KJ866501). s
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204 Subsequent DGGE analyses for AOA, AOB and nifH genes were performed r
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205 using Ingeny PhorU2 system (Ingeny, Goes, the Netherlands), with denaturing gradient n

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206 15-55%, 35-70% and 45-65% respectively (100% denaturant with 7 M urea and 40% ov
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207 formamide) and 6% polyacrylamide (14, 30). The DGGE electrophoresis runs were b
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208 carried out at a temperature of 60⁰C and maintained at 100V for 16 h. After 1
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209 electrophoresis, the gels were stained with SYBR Gold (final concentration of 0.5 mg L- 20
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210 1 Invitrogen, Breda, the Netherlands) and the gels were visualized on a photo- b
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211 documented system under ultraviolet light. u
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213 Data analysis
214 The results of the quantitative PCR were analyzed by one-way ANOVA, and average
215 values were compared based on the Tukey test at a significance level of 0.05 using the
216 R package (RStudio v0.97.312). Additionally, these results were correlated with
217 environmental variables, as soil characteristics, plant genotype and period of the year
218 that the crop was realized (values of temperature and amount of rain;
219 http://sigma.cptec.inpe.br/prec_sat/). Qualitative explanatory variables were
220 transformed into dummy variables before analysis. Physico-chemical variables were
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221 checked for normality and were log-transformed (except for soil pH). The respective
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222 effects of each explanatory variable, or combinations thereof, were determined by a
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223 redundancy variation partitioning analysis in Canoco statistical software (Canoco 4.5, f
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224 Biometris, Wageningen, The Netherlands) (12, 31).

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225 The band matrices, derived from PCR-DGGE patterns, were analyzed to check p:
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226 the data distribution (linear or normal) through detrended correspondence analysis m
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227 (DCA) (32, 33). To correlate the profile obtained with environmental variables (such as s
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228 plant genotype, soil type and period of cultivation), redundancy analysis (RDA) was r
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229 used for data with linear distribution (first gradient on DCA < 3.0), while data with n

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230 normal distribution (first gradient on DCA < 3.0) were analyzed by canonical ov
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231 correspondence analysis (CCA). In order to investigate the significance of the b
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232 correlations between patterns and environmental variables, Monte Carlo permutation 1
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233 test was performed based on 999 random permutations, taking as the null hypothesis 0
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234 that species data were unrelated to environmental data (32, 34). b
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235 The influence of soil parameters on the abundance (qPCR data) of ammonia u
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236 oxidizers and diazotrophic communities was determined by using Pearson’s linear
237 correlation coefficient implemented in SPSS 16.0 (SPSS, Inc., IL, USA).
238
239 RESULTS