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Applied and Environmental Microbiology, August 2006, p. 5181-5189, Vol. 72, No. 8
0099-2240/06/$08.00+0 doi:10.1128/AEM.00231-06
Copyright © 2006, American Society for Microbiology. All Rights Reserved.
INRA-University of Burgundy, Microbiology and Soil Geochemistry, CMSE, 17 rue Sully, B.P. 86510, 21065 Dijon Cedex, France,1 University of Ljubljana, Biotechnical Faculty, Department of Food Science and Technology, Vecna pot 111, 1000 Ljubljana, Slovenia2
Received 30 January 2006/ Accepted 17 May 2006
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N2O emissions are highly variable in soils and are primarily produced by biological nitrification and denitrification, although the latter is considered to be the main source (31). N2O is an intermediate product in the denitrification pathway, which consists of the sequential reduction of NO3 to N2 via the metalloenzymes nitrate reductase, nitrite reductase, nitric oxide reductase, and nitrous oxide reductase (32). Therefore, N2O emission by denitrification is the net result of the balance between production and reduction of N2O by denitrifying bacteria. The N2O reductase (EC 1.7.99.6) is a homodimeric multicopper enzyme, which has been purified from numerous gram-negative denitrifiers but not yet from a gram-positive bacterium (4, 5, 11, 17, 27). Production of N2O by denitrifying isolates as an end product of denitrification has been reported by several authors (2, 3, 7). Sequencing of the complete genome of Agrobacterium tumefaciens C58 revealed the presence of a denitrification cluster with genes encoding the periplasmic nitrate reductase, the copper nitrite reductase, and the nitric oxide reductase, but the genes encoding the N2O reductase were not found within the entire genome (30). These results suggest that N2O production by denitrifiers may be due not only to the regulation of nitrous oxide reductase activity but also to an absence of genes encoding this enzyme in some denitrifying populations.
Since an unknown percentage of denitrifying bacteria lack the genes encoding N2O reductase and will emit N2O as an end product in denitrifying conditions, irrespective of soil physicochemical characteristics, it is important to know the abundance of bacteria able to reduce N2O in order to better understand the key drivers of N2O emissions from soil. Recent papers have underlined the potential role of the composition of the denitrifying community among the factors leading to N2O emission (1, 9).
In the present study, we report the development of a quantitative PCR assay to quantify the nosZ gene encoding the catalytic subunit of N2O reductase. The specificity and sensitivity of the assay were investigated with environmental samples, and the results were compared with those of the real-time quantification of the 16S rRNA, narG (encoding the membrane-bound nitrate reductase), and nirK (encoding the copper nitrite reductase) genes.
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TABLE 1. Properties of the soils analyzed
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TABLE 2. Bacterial strains used in this study to test specificity of the nosZ1 and nosZ2 primers
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Primer design.
Two independent sets of nosZ primers were designed by aligning all publicly available complete nosZ sequences using the Fungene database (http://flyingcloud.cme.msu.edu/fungene/) and searching for conserved regions that could provide suitable primer target sites. Four degenerate primers, nosZ1F-nosZ1R and nosZ2F-nosZ2R, were selected to amplify a 259- and a 267-bp fragment, respectively, within the region amplified using the diversity primers nosZF-nosZR designed by Kloos et al. (13) (Fig. 1). The specificity of the primers was tested in silico using the Fungene software (http://flyingcloud.cme.msu.edu/fungene/) and 42 complete nosZ sequences from known strains. In addition, 15 strains were also used to evaluate primer specificity.
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FIG. 1. Sequences and binding positions of the nosZ1 and nosZ2 primers based on the nosZ sequence from Pseudomonas fluorescens (accession number AF197478). Degenerated sites are in boldface (W = AT, S = CG, Y = CT, M = AC, R = AG, K = GT, and V = ACG).
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FIG. 2. Standard curves of the nosZ1 and nosZ2 assays obtained by plotting the concentration of control DNA versus the cycle number required to elevate the fluorescence signal above the threshold.
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DNA extracts from all soils which exhibit nosZ copy numbers ranging between 102 and 103 copies per ng were spiked with the plasmid DNA at a concentration of 104 to 105 copies per ng, and gene copy numbers were compared to those in samples without soil DNA to test for the potential presence of PCR inhibitors. In addition, serial dilutions of the DNA extracted from soil samples were quantified and compared.
Construction of nosZ quantitative PCR product clone libraries and phylogenetic analysis.
The specificity of the assays was verified by constructing eight clone libraries using the nosZ1 and nosZ2 real-time PCR products from DNA extracted from the Nancy, Champ Noël, Himalaya (6,000-m), and Ljubljana soils. The three replicates of quantitative PCR products from each soil were pooled and cloned into the plasmid vector pGEM-T Easy according to the manufacturer's instructions (Promega, France). Cells were spread onto LB agar plates containing ampicillin and grown overnight at 37°C. The colonies were then randomly picked, transferred to new plates, and incubated overnight at 37°C. Small aliquots of cells from each colony were transferred to a PCR mixture containing the vector primers T7 and SP6. Clones containing the insert DNA were identified by agarose gel electrophoresis. Nucleotide sequences of the inserted quantitative PCR products were determined using the GenomeLab DTCS Quick Start kit (Beckman Coulter) with primer T7 in a Ceq 8000 sequencer, according to the manufacturer's instructions (Beckman Coulter).
One hundred twenty-eight nosZ sequences from the eight clone libraries were deposited in GenBank (accession numbers given below). Alignments of nosZ fragments of 259 and 267 nucleotides from quantitative PCR products and from reference strains were made by using the CLUSTAL X software version 1.0.1. The neighbor-joining method was used to calculate the distances and to construct phylogenic trees.
Data analysis.
For each soil replicate, quantitative PCR was performed twice for each gene. Replicate results of quantitative PCR measurements were averaged (n = 6), and the standard error was calculated. Comparison of the gene copy numbers within the same soil and between soils was performed using the Fisher test in StatView version 5.0 (SAS Institute Inc.).
Nucleotide sequence accession numbers.
The 128 nosZ sequences from the eight clone libraries were deposited in GenBank under accession numbers AJ786667 to AJ786710.
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TABLE 3. narG, nirK, and nosZ (obtained with nosZ1 and nosZ2 assays) calculated percentages of 16S rRNA copy numbers based on the gene copy number per ng of DNA
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FIG. 3. Melting-curve profiles for the amplicons of environmental DNA obtained by nosZ1 (a) and nosZ2 (b) primer sets.
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We then compared the 16S rRNA and nosZ gene copy numbers to check that the standard curves gave a good estimation of the latter, using genomic DNA from Bradyrhizobium japonicum USDA110 as the template. Quantification of the gene copy number in 12.5 ng of DNA from B. japonicum using the nosZ1, nosZ2, and 16S rRNA quantitative PCR assays gave the same copy number of approximately 106. The experimental number was in accordance with the theoretical number estimated using an average molecular mass of 660 for a base pair in double-stranded DNA, the number of 16S rRNA and nosZ gene copies in the B. japonicum genome (one each), the genome size of B. japonicum of 9,105,828 bp (genome accession number NC 004460), and the spectrophotometrically determined concentration of genomic DNA.
Detection limit.
In our SYBR green assay, it was possible to discriminate against the primer dimer fluorescence by acquiring data at a temperature of 80°C, which is above the melting point of these by-products. This temperature was determined and verified by melting-curve analysis (Fig. 3). The gene copy numbers in the NTCs were 0 and less than 10 copies for nosZ1 and nosZ2, respectively. Higher values of 102 copies per assay were observed for narG and 16S rRNA quantification. According to the NTC values, a detection limit of approximately 10 to 100 target molecules per assay was achieved for nosZ quantification, which corresponds roughly to 103 to 104 targets per gram of dry soil.
Quantification of the 16S rRNA, narG, nirK, and nosZ genes.
The applicability of the assay to quantify the nosZ gene in environmental samples was evaluated using DNA extracted from various soils as the template. No significant difference between the estimated nosZ gene copy numbers based on the nosZ1 or nosZ2 primer was recorded in any of the tested soils. The nosZ density in the Himalayan soil ranged from 2 x 105 to 5 x 105 copies g1 of dry soil whatever the sampling site, whereas densities up to 107 copies g1 of dry soil were observed in the French soils (Fig. 4). The reproducibility of two independent quantitative PCR assays with the same DNA extract was good, with average percentages of variation of 17% and 28% for nosZ1 and nosZ2, respectively (data not shown). The nirK gene density was between 106 and 107 copies g1 of dry soil for all soils except that of Champ Noël, in which 2.5 x 108 copies g1 of dry soil were quantified. This latter soil also exhibited significantly higher 16S rRNA and narG gene copy numbers (Fig. 4). The relative abundance of nosZ genes ranged from 0.1 to 0.5% of 16S rRNA genes, except in the soil from Nancy, where it was about 4% (Table 3). A slightly higher span of relative abundance (0.7 to 6% of 16S rRNA genes) was observed for the nirK genes.
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FIG. 4. 16S rRNA, narG, nirK, and nosZ (obtained with nosZ1 and nosZ2 assays) copy numbers g1 of dry soil in the different soils. Error bars indicate standard errors of the two independent PCRs of the three replicate DNA extractions. Significantly different values (P < 0.05) between different genes in the same soil are marked by capital letters (A to C) under the columns, and significantly different values (P < 0.05) between different soils for the same gene are marked by lowercase letters (a to c).
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Phylogenetic analysis of nosZ quantitative PCR products.
The applicability of the primers to environmental samples was verified by performing a phylogenetic analysis of the sequenced quantitative PCR products. The tree topology differed between the nosZ sequences from nosZ1 and nosZ2 sets of primers (Fig. 5 and 6). Analysis of the nosZ1 tree showed a large highly conserved group of sequences clustering next to the nosZ sequence from ß-proteobacteria such as Ralstonia solanacearum and Cupriavidus metallidurans and a group of sequences close to nosZ genes from
-proteobacteria. Sequences obtained with the nosZ2 primers fell within three clusters, with most of the sequences clustering with nosZ from
-proteobacteria (Fig. 6). The second cluster encompassed sequences from all soils except Ljubljana and nosZ sequences from
-proteobacteria such as Pseudomonas spp. The last cluster contained the sequences from Nancy and Ljubljana marsh and nosZ from ß-proteobacteria.
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FIG. 5. Phylogenetic tree of nosZ quantitative PCR products obtained with the nosZ1 primers and of nosZ genes from reference strains. Fragments of 259 nucleotides from the quantitative PCR products and from reference strains were used to calculate the tree. The tree is based on distance matrix analysis and the neighbor-joining method. Bootstrap values greater than 700 from 1,000 replicate trees are reported at the nodes. The sequence of nosZ from Wolinella succinogenes served as an outgroup to root the tree.
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FIG. 6. Phylogenetic tree of nosZ quantitative PCR products obtained with the nosZ2 primers and of nosZ genes from reference strains. Fragments of 267 nucleotides from the quantitative PCR products and from reference strains were used to calculate the tree. The tree is based on distance matrix analysis and the neighbor-joining method. Bootstrap values greater than 700 from 1,000 replicate trees are reported at the nodes. The sequence of nosZ from Wolinella succinogenes served as an outgroup to root the tree.
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In order to relate with more accuracy the diversity and density data in future studies, quantitative PCR primers were designed in the regions flanking the nosZ fragment amplified for diversity analysis (13). In addition, two independent sets of primers, for nosZ1 and nosZ2, were used to verify the robustness of our assay. Since between 0 and fewer than 10 targets were detected in the no-template control, the detection limit of our nosZ assays was equivalent to 103 to 104 copies g1 of dry soil, which was within the range of those previously reported (8, 14, 29). The standard curves were linear over 6 logs for both nosZ1 and nosZ2, with a very good correlation between the number of copies of target DNA and the cycle threshold value (Fig. 2). Quantification of nosZ in DNA from Bradyrhizobium japonicum USDA110 using either the nosZ1 or the nosZ2 set of primers gave no significant difference with the theoretical nosZ gene copy number of approximately 100,000 copies per ng of DNA, indicating that both the nosZ1 and nosZ2 assays can be used to accurately quantify nosZ. To further increase the robustness of the assays and facilitate the comparison of data obtained with the two sets of primers, three standard plasmids were constructed, one specific to each set of primers and one containing a 699-bp nosZ fragment that can be used for both sets of primers (Fig. 1).
Primer specificity was verified by amplifying a collection of denitrifiers and by sequencing the real-time PCR products from the soil samples. None of the nosZ primers tested in this study was able to amplify the Bacillus strains, indicating that our primers were probably specific only for the nitrous oxide reductase from gram-negative bacteria. In addition, nosZ sequences from a few strains, such as the
-proteobacterium Wolinella succinogenes (25), exhibit too many mismatches with either the nosZ1 or nosZ2 primers to be successfully amplified. Analysis of the nosZ1 and nosZ2 phylogenetic trees showed different topologies, thereby confirming the differences in specificity between the two sets of nosZ primers. Most of the sequences amplified by nosZ1 clustered with nosZ from ß-proteobacteria (Fig. 5), whereas the sequences obtained with the nosZ2 primers were more widely spread between clusters containing nosZ from
-proteobacteria and those containing nosZ from ß-proteobacteria. Some sequences also clustered with nosZ from
-proteobacteria (Fig. 6). A larger number of sequences was generated for the French soils from Nancy and Champ Noël to allow their comparison with sequences obtained by amplifying the same soils with the nosZ primers described by Kloos et al. (13; unpublished data). Comparison of the phylogenetic trees showed that sequences from the nosZ2 assay were more closely related to those obtained using the nosZ primer from Kloos et al. (13) than to those obtained using the nosZ1 primer (data not shown). Altogether, these data confirm that the diversity results obtained in PCR-based studies are strongly influenced by the initial choice of primer set. Analysis of the quantitative PCR products confirmed that at least the nosZ2 set of primers was capable of quantifying the nosZ gene from
-, ß-, and
-proteobacteria in soils. Based on the intuition that the primer set yielding the greater diversity would be more suitable, the nosZ2 primers seemed of greater interest than the nosZ1 primers. However, the superiority of either primer set cannot be confirmed since the real nosZ diversity in the studied soils (i.e., determined without any PCR or cultivation bias) is still unknown.
Although differences in specificity were observed between the nosZ1 and nosZ2 primers, similar nosZ1 and nosZ2 gene copy numbers were observed in each soil. Thus, application of the nosZ quantitative PCR assay to template DNA extracted from different soils showed that the numbers of nosZ genes ranged from 105 to 107 copies g1 of dry soil (Fig. 4). The numbers of nirK copies were in the upper range of those found previously by Henry et al. (8) but 1 to 2 orders of magnitude lower than those observed by Qiu et al. using competitive PCR (22). Similar 16S rRNA gene copy numbers were also observed by Smith et al. (26). Up to now, only one copy of the nirK and nosZ genes has been observed in all the bacteria studied (19), suggesting that the nirK and nosZ gene copy numbers are directly correlated with cell numbers. Since denitrifiers generally contain either a copper nitrite reductase or a cytochrome cd1 nitrite reductase (32), the nosZ gene copy number is expected to be higher than the nirK gene copy number. However, quantification of nirK showed numbers on the same order of magnitude as nosZ or even 10 times higher in the soil from Champ Noël. This higher nirK gene copy number could be related to methodological bias, because nirK primers might be more universal than the nosZ primers. However, phylogenetic analysis of the sequenced quantitative PCR products showed that the nosZ fragments related to nosZ from
-, ß-, and
-proteobacteria were successfully amplified, which demonstrated that our primers are not restricted to a narrow group. Another hypothesis to explain these high nirK copy numbers is that a significant percentage of denitrifiers present in soil lack the nosZ gene, as has been demonstrated by sequencing the complete genome of Agrobacterium tumefaciens C58 (30). Therefore, it is tempting to suggest that the variations in nirK/nosZ ratio depending on the soil could be associated with differences in the proportion of denitrifiers lacking nosZ. In future studies, it will be interesting to test this hypothesis and its ecological consequences in terms of greenhouse gas emission by estimating the nirK- and/or nirS-to-nosZ ratio in relation to the ability of the soil to produce N2O.
To evaluate the abundance of denitrifiers relative to total bacteria, the percentages of denitrification genes in proportion to 16S rRNA were calculated. Such calculation was possible due to (i) the similar PCR efficiencies for the different assays and (ii) the use of the same amount of DNA from B. japonicum as a control for the 16S rRNA, nirK, and nosZ assays. Analysis of the percentages of nirK and nosZ in relation to 16S rRNA genes showed very small amounts, between 0.1 and 6%, for both genes (Table 3). Assuming that the 16S rRNA copy number in bacteria varies from 1 to 13 (6), these percentages are in agreement with previous results from cultivation studies showing that the densities of denitrifiers were 2 orders of magnitude lower than those of the total bacteria (2). Similarly, Tiedje (29) reported a denitrifier percentage of the total population ranging between 0.1 and 5%. In contrast, higher ratios of narG to 16S rRNA, up to 40%, were observed. While the 16S rRNA, nirK, and nosZ primers were designed to be as universal as possible, the narG primers used in this study were designed to be specific to a new group of nitrate reducers (15). Even though the narG copy number in this new group is unknown, it does not exceed three copies in known genomes (19). These high percentages of this unknown group of nitrate reducers are in accordance with other reports of their numerical importance in the soil (15). However, from an ecological perspective it is interesting that this novel narG group was less abundant in the three samples from the Himalayas than in all the other soils tested in this study.
In conclusion, the quantitative nosZ PCR assay, which was developed in this study, showed that the N2O-reducing community represented less than 5% of the total bacteria in the studied soils. Since our understanding of microbial communities should be not only qualitative but also quantitative, there is a need in microbial ecology to quantify these microbial populations using cultivation-independent methods to link the diversity and density of the microbial community with its activity (21). The results presented in this study confirm that quantitative PCR, which is specific, sensitive, and rapid, can be used in microbial ecology to quantify genes in large numbers of environmental samples.
We thank COST856 "Ecological Aspects of Denitrification, with Emphasis on Agriculture" (http://www.cost856.de) for funding the short-term scientific mission of B. Stres in Dijon. This work was supported by the French Ministry of Research (ACI PNBC "MUTEN") and by the Burgundy Region.
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tin, and J. M. Tiedje. 2004. Nitrous oxide reductase (nosZ) gene fragments differ between native and cultivated Michigan soils. Appl. Environ. Microbiol. 70:301-309.This article has been cited by other articles:
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