J Soils Sediments DOI 10.1007/s11368-017-1792-3
SOILS, SEC 5 • SOIL AND LANDSCAPE ECOLOGY • RESEARCH ARTICLE
Ammonia-oxidizing archaea and bacteria responding differently to fertilizer type and irrigation frequency as revealed by Illumina Miseq sequencing Ya-Dong Yang 1 & Yong-Feng Ren 1 & Xi-Quan Wang 1 & Yue-Gao Hu 1 & Zhi-Min Wang 1 & Zhao-Hai Zeng 1
Received: 22 May 2017 / Accepted: 18 July 2017 # Springer-Verlag GmbH Germany 2017
Abstract Purpose Ammonia oxidation, the first and rate-limiting step of nitrification, can be strongly influenced by agricultural practices, but little is known about the effects of fertilization and irrigation combination on ammonia oxidizers in agricultural soils. This study was designed to reveal how fertilizer type and irrigation frequency affect the ammonia-oxidizing archaea (AOA) and bacteria (AOB) communities in a northern Chinese wheat-maize rotation soil. Materials and methods Soil samples were collected from a long-term field experiment under different fertilization and irrigation regimes located in Wuqiao Experimental Station of China Agricultural University in June 2016. The abundance, diversity, and composition of AOA and AOB in the soils were investigated by using real-time PCR and Illumina Miseq sequencing approaches. Results and discussion The abundance of AOA was higher in the irrigated treatments, but lower in the treatments without irrigation, than that of AOB. The AOA abundance was positively correlated with soil moisture, pH, and NO3−-N, while the AOB abundance was positively correlated with TN and NO3−-N. Soil potential nitrification activity (PNA) was significantly positively correlated with the AOB abundance. Both fertilizer type and irrigation frequency significantly affected Shannon, ACE, and Chao1 indices of the AOB community, while only irrigation frequency had a significant impact on Responsible editor: Jizheng He Ya-Dong Yang and Yong-Feng Ren contributed equally to this work. * Zhao-Hai Zeng
[email protected] 1
College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
Shannon index of the AOA community. PCoA analysis results indicated that irrigation frequency greatly affected the AOA community structure, while fertilizer type played a more important role in affecting the AOB community structure. Mantel test and correlation heatmap analysis results indicated that soil moisture, pH, and NH4+-N were significantly correlated to the AOA community structure, and TN and SOC were significantly correlated to the AOB community structure. Conclusions This study demonstrated that irrigation frequency greatly influenced the AOA community, while fertilizer type had a stronger effect on the AOB community. It was AOB but not AOA played a more important role in soil nitrification. Moreover, soil moisture, pH, and TN were the main determinants in driving the AOA community and TN and SOC were the main factors in influencing the AOB community. Keywords amoA gene . Ammonia-oxidizing archaea (AOA) . Ammonia-oxidizing bacteria (AOB) . Illumina Miseq sequencing . Irrigation frequency . Manure fertilizer
1 Introduction Nitrification, a microbial process converting ammonia to nitrate via nitrite, is a key component of the global N cycle (Gruber and Galloway 2008) and regulates the fertilizer use efficiency, as well as the N losses from soil through NO2− and NO3− leaching into groundwater and emissions of greenhouse gas (Kowalchuk and Stephen 2001; Wrage et al. 2001). The oxidation of ammonia to nitrite is the primary and ratelimiting step in nitrification and is performed by the ammonia-oxidizing bacteria (AOB) belonging to the betaand/or gamma-proteobacteria (Purkhold et al. 2000; Kowalchuk and Stephen 2001) and ammonia-oxidizing
J Soils Sediments
archaea (AOA) belonging to the phylum Thaumarchaeota (Brochier-Armanet et al. 2008; Pester et al. 2011; Zhang and He 2012; Monteiro et al. 2014). Both AOA and AOB harbor the ammonia monooxygenase (AMO) which catalyzes the ammonia oxidation process. The α-subunit of the enzyme AMO is encoded by the amoA gene which is generally used as a biomarker in ammonia oxidizer studies (Rotthauwe et al. 1997). However, the amoA genes from AOA and AOB are sufficiently divergent in evolutionary. Increasing evidence have demonstrated that AOA is ubiquitously distributed and dominate in abundance over AOB in most terrestrial environments, especially in agricultural soils (Leininger et al. 2006; He et al. 2007; Zhou et al. 2014), suggesting that AOA might play a more important role than AOB in these soils. It is reported that AOA were more abundant than AOB in strongly acidic soils and it was AOA but not AOB responsible for the nitrification (Zhang et al. 2012). However, some studies confirmed that it is numerically occupied by AOA but functionally dominated by AOB in agricultural soils (Shen et al. 2008; Jia and Conrad 2009), indicating that the numerical dominance is often not equated with the functional importance in ammonia oxidization. Hence, the relationship between AOA and AOB abundance and their relative contributions to nitrification differ in different soil conditions. Studies have indicated that the abundance and composition of AOA and AOB shift in response to various environmental factors (Chu et al. 2007; Nicol et al. 2008; Wu et al. 2011; Chen et al. 2013; Zhou et al. 2014). Long-term N fertilization greatly changed the abundance and composition of AOA in acidic soils (He et al. 2007; Wessén et al. 2010) but significantly affected the AOB abundance and composition in an alkaline sandy soil (Shen et al. 2008). Enwall et al. (2005) reported that there were significant differences in the AOB community among different fertilization regimes, and the highest diversity of AOB was detected in the manure fertilization soil. Wang et al. (2014) revealed that manure fertilization increased AOB rather than AOA abundance in paddy soils. Nonetheless, Nyberg et al. (2006) suggested that fertilization had no evident impact on the composition of ammonia oxidizers in soil incubation experiments. In addition, soil moisture also affected the abundance and composition of ammonia oxidizers (Singh and Kashyap 2006; Szukics et al. 2012; Chen et al. 2013; Hu et al. 2015). Precipitation dramatically altered the abundance and composition of AOB rather than AOA in a typical steppe (Chen et al. 2013), but water addition increased the abundance of AOA but not AOB in dry sub-humid ecosystems (Szukics et al. 2012; Hu et al. 2015). On the other hand, Hartmann et al. (2013) revealed that drought had no apparent impact on the abundance of ammonia oxidizers in grassland soils. Numerous studies have been carried out to investigate the effects of fertilizer type and soil moisture on ammonia oxidizers, but most of them were done
separately. The interactive effect of fertilizer type and irrigation frequency on the abundance, diversity, and composition of AOA and AOB remains unclear in agricultural soils. In order to evaluate the impacts of fertilizer type, irrigation frequency, and their interaction on the abundance, diversity, and composition of AOA and AOB, a long-term field experiment with two fertilizer types and three irrigation frequency levels was conducted in a northern Chinese wheat-maize rotation soil. Real-time PCR and Illumina MiSeq sequencing approaches were used to reveal the abundance, diversity, and composition of AOA and AOB in the soils by targeting the amoA gene. We aimed to investigate (i) how AOA and AOB responding to fertilizer type and irrigation frequency and (ii) which soil properties are the key factors resulting in the difference in abundance, diversity, and composition of AOA and AOB in different soil conditions.
2 Materials and methods 2.1 Field site description The field site was located in Wuqiao Experimental Station of China Agricultural University (37°37′N, 116°23′E) in Hebei province, P. R. China. The study site has a warm temperate semi-humid continental monsoon climate with a mean annual temperature of 12.6 °C and precipitation of 562 mm. The soil is classified as a Calcaric fluvisol with a sandy clay loam texture (FAO 1974). The long-term fertilization and irrigation experiment started in 2005 in northern China with a rotation of wheat-maize and maintained the same fertilization and irrigation regimes every year since then during the wheat growing season, including six treatments: synthetic N fertilization and no irrigation, CI0; synthetic N fertilization and irrigated at the jointing stage, CI1; synthetic N fertilization and irrigated at the jointing and filling stages, respectively, CI2; manure fertilization and no irrigation, MI0; manure fertilization and irrigated at the jointing stage, MI1; and manure fertilization and irrigated at the jointing and filling stages, respectively, MI2; with three replicates for each treatment in a randomized plot design. The fertilizers were 225 kg (NH2) 2CO, 300 kg (NH4)2HPO4, and 150 kg K2SO4 fertilizers per ha for the synthetic N fertilization treatments and 22.5 m3 fowl manure per ha for the manure fertilization treatments, respectively. All fertilizers were applied in wheat growing season as base fertilizer. The irrigation volume was 750 m3 ha−1 each time, and all treatments received a volume of 750 m3 ha−1 irrigation before wheat sowed. 2.2 Soil sampling Soil samples (0–20 cm) were collected in June 2016 when winter wheat was harvested. Five soil cores were taken from
J Soils Sediments
each replicate plot and mixed together to get one composite sample. All soils were passed through a 2.0-mm sieve to remove roots and sundries and then divided into two parts: one for soil chemical property analysis and the other was stored at −80 °C for the DNA extraction. 2.3 Soil chemical property analysis and PNA Soil moisture was measured by oven-drying at 105 °C for 24 h. Soil pH value was measured using a pH meter (FE28, Mettler Toledo, USA) using a soil to water ratio of 1:2.5 (m/v). Soil organic carbon and total nitrogen contents were determined using the K2Cr2O7 oxidation-reduction titration method and Kjeldahl digestion method (Bao 2000), respectively. The NH4+-N and NO3−-N concentrations were extracted from fresh soil with 2 M KCl and detected using a Continuous Flow Analyzer (Skalar + Analytical, Holland, The Netherlands). Soil PNA was determined according to the standard protocol described by Hart et al. (1994). Briefly, 10 g of fresh soil was placed in a 250-mL Erlenmeyer flask with 100 mL of a 1.5 mM NH4+ and 1 mM phosphate buffer with the pH adjusted to 7.2. The slurry was shaken on a shaker at 180 rpm for 24 h at 25 °C to maintain aeration in the dark. Aliquots of 5 mL were subsequently removed using a pipette at 2, 6, 12, and 24 h after the start of the incubation. The aliquots were then centrifuged, and the supernatant was filtered and stored at −80 °C until analysis. The NO3−-N concentrations were determined using a Continuous Flow Analyzer (Skalar + Analytical, Holland, The Netherlands), after which PNA was calculated from the rate of linear regression of NO3−-N concentrations over time (mg NO3−-N g−1 h−1). 2.4 DNA extraction and real-time PCR DNA was extracted from 0.3 g of fresh soil using the E.Z.N.A.® Soil DNA Kit for soil (Omega, GA, USA) according to the manufacturer’s instructions. The DNA extract was checked on 1% agarose gel, and DNA concentration was determined with a NANO Quant (Tecan, Männedorf, Switzerland). For real-time PCR, the primers Arch-amoAF/Arch-amoAR (Francis et al. 2005) and amoA1F/ amoA2R (Rotthauwe et al. 1997) were used for AOA and AOB, respectively. Real-time PCR amplification was performed on an ABI 7500 thermocycler (ABI, CA, USA) using the SYBR® Premix Ex Taq™ (TaKaRa, Dalian, China) according to the manufacturer’s instructions, with 1 μL DNA extract (1–10 ng) as the template in 25-μL reaction mixtures. The program was 94 °C (5 min), followed by 40 cycles of 94 °C (30 s), 53/55 °C (30 s) and 72 °C (1 min), and 72 °C (5 min) for the last cycle for AOA and AOB, respectively. For standard curves, plasmids containing archaeal and bacterial amoA genes were used as standards for AOA and AOB,
respectively. Real-time PCR was done in triplicate and the amplification efficiency and R2 were 80.2%, 0.991 and 82.5%, 0.994 for AOA and AOB, respectively. 2.5 Illumina Miseq sequencing The PCR amplification was performed on an ABI GeneAmp® 9700 PCR thermocycler (ABI, CA, USA). The archaeal and bacterial amoA genes were amplified by PCR using the primers Arch-amoAF/Arch-amoAR and amoA1F/ amoA2R for AOA and AOB, with an eight-base sequence barcode unique to each sample at the 5′ end of Arch-amoAF and amoA1F, respectively. The PCR mixtures contain 5× TransStart FastPfu buffer 10 μL, forward primer (10 μM) 1 μL, reverse primer (10 μM) 1 μL, 2.5 mM dNTPs 5 μL, TransStart FastPfu DNA Polymerase 1 μL, template DNA
