Hans-Peter Horz, Ph.D.1, Richard Kurtz, Ph.D.2, David Batey, Ph.D.2
and Brendan Bohannan, Ph.D.1
1Department of Biological Sciences, Stanford University, Stanford, CA
2MJ Research, Incorporated, South San Francisco, CA
The levels of the amoA gene were used to measure the ammonia-oxidizing bacteria (AOB) population in soils maintained under 16 environmental regimes. DNA was extracted from soil samples and amoA levels analyzed by real-time quantitative PCR (qPCR) using SYBR Green I (SGI) detection chemistry on an MJ Research DNA Engine Opticon 2 continuous fluorescence detection system. Representative samples from the sixteen treatment groups showed amoA levels to vary over a 32-fold range.
Microorganisms play a major role in the biogeochemical cycling of key elements. Numerous research groups have described bacterial diversity in natural environments and their changes over time and space.1, 2, 3 Little is known, however, about the impact of global environmental change on the microbial community in soil. To address this question, the Jasper Ridge Global Change Project (JRGC) simulates global change on a California grassland by the simultaneous manipulation of four major environmental factors: temperature, ambient CO2 concentration, precipitation, and nitrogen deposition, both individually and in combination.4 The JRGC study tests the hypothesis that specific environmental conditions affect the population size of ammoniaoxidizing bacteria (AOB).
AOB are responsible for the oxidation of ammonia to nitrite in the nitrification process. This process is essential for making nitrogen available to most plants. The first step of nitrification, the oxidation of ammonia to hydroxylamine, is catalyzed by amoA, the alpha subunit of ammonia monooxygenase found only in ammonia-oxidizing bacteria.5
To quantitate AOB populations, we developed a real-time qPCR assay for the amoA gene that uses SYBR Green I as an indicating fluorophore.6 Levels of amoA were determined for samples from each of sixteen soiltreatment groups. Each group was exposed to a different combination of two levels of each of the four environmental factors described above. A full report of this research has been submitted for publication.7
Materials and Methods
Experimental facility. The JRGC research facility and complete experimental design for this study are described in references 4 and 7.
DNA Extraction from Soil
Four soil cores from each subplot were extracted aseptically to a depth of 15cm with a 2.2-cm diameter corer. The cores were taken in late April, at the end of the second growing season of the experiment. The UltraClean Soil DNA Kit (Mo Bio Laboratories, Solana Beach, CA) was used to extract total DNA from a 0.5g sub-sample of the consolidated cores.
All DNA samples were analyzed in triplicate. Volumes of individual components and final reaction concentrations are listed in Table 1. SGI was from Molecular Probes (S-7567). MasterAmp PCR premix F was from Epicentre Technologies (MHF-925F). AmpliTaq was from Applied Biosystems (4338856). Reaction components were assembled in white-shell/white-well Hard-Shell microplates (MJ Research #HSP- 9655) and sealed with ultra-clear strip caps (MJ Research TCS-0803).
Plates were transferred to the DNA Engine Opticon 2 system (MJ Research) following reaction assembly. Amplification was performed in calculated control mode according to the cycling program listed in Table 2. The optimal primer-annealing temperature was determined experimentally using the temperaturegradient feature of the DNA Engine Opticon 2 system. Melting curve analysis was performed to assess reaction specificity and to distinguish amplification products. The temperature at which fluorescence was measured during each cycle was set approximately 3C below the Tm of the amplicon to minimize any signal from non-specific amplification.8
Nested primer sets were used for the two rounds of PCR. For the first round, a 672bp fragment from amoA target gene was amplified using the primers: forward, 5'-GGN-GAC-TGG-GAC-TTC-TGG-3', and reverse, 5'-CCC-CTC-KGS-AAA-GCC-TTC-TTC-3'. (N = A, C, G, or T; K = G or T; S = C or G). For the second round of PCR the following primers amplified a 491bp amplicon from the first round PCR product: forward, 5'-GGG-GTT-TCT-ACT-GGT-GGT-3', and reverse, 5'- CCC-CTC-KGS-AAA-GCC-TTC-TTC-3'.
As an internal control, a plasmid DNA template (pUC19 from Invitrogen Corp.) was mixed with 0.25l of DNA extracted from each soil sample, and was subjected to the real-time qPCR protocol designed for amoA (Table 2). This method controls for possible interference and PCR inhibition from substances in the soil DNA samples. The following primer set was used to amplify a 200bp amplicon from the pUC plasmid in both the primary- and the nested-PCR reactions: forward, 5'-GTA-AAA-CGA-CGG-CCA-G-3', and reverse, 5'-CAGGAA- ACA-GCT-ATG-AC-3'.
The threshold line (for determining C(t)) was set manually to 0.015 fluorescence units for all experiments, using the Opticon Monitor software (MJ Research). This threshold is automatically applied to all wells for consistent analysis of individual samples and standards.
All samples were analyzed in triplicate. The cycle threshold (C(t)) values for amoA were determined for each sample and for the control plasmid- DNA template. The amoA target was normalized to the plasmid-DNA control using the following calculation: ΔC(t)sample = average-C(t)amoA average-C(t)plasmid-DNA. The normalized sample C(t) values were then referenced to one soil sample (the calibrator) to determine the relative effect of the environmental treatments on AOB levels. The formula used for determining relative amoA levels is as follows: ΔΔC(t)sample = ΔC(t)sample ΔC(t)calibrator. The amount of amoA for each soil sample is reported as a ratio relative to the calibrator using the following formula: 2ΔΔC(t) (ref. 9).
Relative Quantification of amoA Levels for Soil Plots
Each of the 16 samples presented in this report was subjected to a different combination of environmental factors: temperature, CO2, precipitation, and nitrogen deposition. Table 3 shows the mean C(t) standard deviation as well as successive calculations for relative quantification of the amoA gene in four representative samples. Note that sample 1 has been designated as the calibrator to which the other three samples were normalized. The standard deviation for triplicate measures of each sa mple ranged from 0.07 to 0.31, demonstrating the precision of this method of detection.
The graph in Figure 1 plots relative quantification of the amoA gene for the 16 soil samples and indicates the environmental treatments for the corresponding soil plots. For these representative samples, relative levels of the amoA gene ranged from as low as 0.167 (sample 16) to as high as 5.24 (sample 9), a 32-fold difference.
In this study, DNA was successfully extracted from soil samples and the relative amounts of amoA were determined. The real-time qPCR procedure was used to reliably quantify amoA across a 32-fold range in the 16 representative samples, well within the dynamic range of detection of the DNA Engine Opticon 2 system.10 The 32-fold range of amoA levels in the samples suggests a dramatic impact of different environmental stimuli on the population size of AOB. A complete description of the experimental design and statistical analysis of the larger sample set collected from the different environmental treatment groups can be found in Horz et al. (2004).7
Advantages of Real-time PCR to Analyze Population Size
Real-time qPCR provides several advantages for quantification of gene levels. The sensitivity and dynamic range of detection for this method enables analysis of both low- and high- abundance targets within a sample set.10, 11 The specificity and high throughput of the assay allows gene sequences in DNA from small biomass samples to be detected efficiently in a large number of samples. Primer sets for other specific functions or for individual taxons should allow the effects of environmental changes on population levels to be evaluated for a wide variety of microorganisms.
The use of real-time qPCR in environmental microbiology is a novel and
potentially powerful application of molecular biology to environmental
science. The high degree of accuracy and robustness of the real-time qPCR
technique combined with the advantages of high throughput and reduced
assay costs make this method invaluable for the analysis of microbial
1. DeLong, E.F. Archaea in coastal marine environments. Proc. Natl. Acad. Sci. 89: 5685- 5689 (1992).
2. Giovannoni, S.J., Britschgi, T.B., Moyer, C.L., and Field, K.G. Genetic diversity in Sargasso Sea bacterioplankton. Nature 345: 60-63 (1990).
3. Wagner, M.A., Roger, A.J., Flax, J.L., Brusseau, G.A., and Stahl, D.A. Phylogeny of dissimilatory sulfite reductases supports an early origin of sulfate respiration. J. Bacteriol. 180: 2975-2982 (1998).
4. Shaw, M.R., Zavaleta, E.S., Chiariello, N.R., Cleland, E.E., Mooney, H.A., and Field, C.B. Grassland responses to global environmental changes suppressed by elevated CO2. Science. 298:1987-1990 (2002).
5. Hollocher, T. C., Tate, M. E., and Nicholas, D. J. Oxidation of ammonia by Nitrosomonas europaea: definitive 18O-tracer evidence that hydroxylamine formation involves a monooxygenase. J. Biol. Chem. 256:1083410836 (1981).
6. Morrison, T.B., Weis, J.J., and Wittwer, C.T. Quantification of low-copy transcripts by continuous SYBR Green I monitoring during amplification. Biotechniques 24: 954-958 (1998).
7. Horz, Hans-Peter and Bohannan, Brendan. (submitted).
8. Optimal plate read temperature for real-time PCR with SYBR Green I. MJ Research Technical Note #004.
9. Gene Expression Profiling from Human Tissue Using RT-qPCR with SYBR Green I Dye on the DNA Engine Opticon System. MJ Research Application Note Vol 1, No 3.
10. Real-time Detection and Quantification using the DyNAmo SYBR Green qPCR Kit. Application Note Vol. 2, No. 9, MJ Research.
11. Bustin, S.A. Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. Journal of Molecular Endocrinology. 25: 169-193. (2000)
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