Analysis of bacterial communities on alkaline phosphatase genes in soil supplied with organic matter

Abstract

We studied the effects of the application of organic matter (OM) and chemical fertilizer (CF) on soil alkaline phosphatase (ALP) activity and ALP-harboring bacterial communities in the rhizosphere and bulk soil in an experimental lettuce field in Hokkaido, Japan. The ALP activity was higher in soils with OM than in soils with CF, and activity was higher in the rhizosphere for OM than in the bulk soil. Biomass P and available P in the soil were positively related to the ALP activity of the soil. As a result, the P concentration of lettuce was higher in OM soil than in CF soil. We analyzed the ALP-harboring bacterial communities using polymerase chain reaction based denaturing gradient gel electrophoresis (DGGE) on the ALP genes. Numerous ALP genes were detected in the DGGE profile, regardless of sampling time, fertilizer treatment or sampled soil area, which indicated a large diversity in ALP-harboring bacteria in the soil. Several ALP gene fragments were closely related to the ALP genes of Mesorhizobium loti and Pseudomonas fluorescens. The community structures of the ALP-harboring bacteria were assessed using principal component analysis of the DGGE profiles. Fertilizer treatment and sampled soil area significantly affected the community structures of ALP-harboring bacteria. As the DGGE bands contributing to the principal component were different from sampling time, it is suggested that the major bacteria harboring the ALP gene shifted. Furthermore, there was, in part, a significant correlation between ALP activity and the community structure of the ALP-harboring bacteria. These results raise the possibility that different ALP-harboring bacteria release different amounts and/or activity of ALP, and that the structure of ALP-harboring bacterial communities may play a major role in determining overall soil ALP activity.

Key words:

• alkaline phosphatase
• bacterial community structure
• DGGE
• organic matter
• rhizosphere

INTRODUCTION

A major problem with the use of phosphorus (P) fertilizer is the low recovery rate of P from the fertilizer to the plants; only 10–20% of applied P is available to plants in the year of application (Holford 1997; Mishima et al. 2006). The majority of applied P is rapidly fixed to the soil, where it is poorly available to plant roots (Sanyal and De Datta 1991). Global consumption of P-based fertilizers currently exceeds 30 million tones of P₂O₅ annually and, thus, the world's known reserves of high-quality rock phosphate will be consumed within the next 80 years (Isherwood 2000). Beyond this time, the production of P-based fertilizers will require the processing of lower-grade rock phosphates at significantly higher cost. Furthermore, as P losses from farm fields have serious environmental and ecological problems, it is necessary to develop better management of P in agricultural systems (Tunney et al. 1997). Soil microorganisms have been recognized as playing a major role in many processes involving P transformations in soil (Birch 1961). Using microbial associations to improve the efficiency of plant access to P from soil would be of considerable economic and environmental benefit.

Organic P in soil generally accounts for 30–50% of total soil P (Dalal 1978). Plants are unable to take up organic P directly from the soil and phosphatases are required to mineralize organic P to release plant-available P (Richardson 2001). Phosphatases (phosphoric monoester hydrolases) are classified as acid phosphatase or alkaline phosphatase (ALP) by their optimum pH. Plant roots are known to be major producers of acid phosphatase (Dinkelaker and Marschner 1992; Speir and Cowling 1991), but do not produce ALP (Nakas et al. 1987; Tarafdar and Claassen 1988). Alkaline phosphatase originates from soil bacteria, fungi and fauna (Nakas et al. 1987; Tarafdar and Claassen 1988). The application of organic matter to soil is known to increase ALP activity (Lee et al. 2004; Mandal et al. 2007; Yang et al. 2006), and Mandal et al. (2007) reported that significantly greater ALP activity in organic matter treated soils might be because of the enhanced diversity of phosphate-solubilizing bacteria. To date, there is no clear indication of the relationship between the diversity of ALP-producing bacteria and ALP activity in the soil.

Recently developed molecular biological methods enable the characterization of microbial communities in environmental samples without any culturing step (Dobrovol'skaya et al. 2001; Kennedy and Gewin 1997; Rondon et al. 1999). Denaturing gradient gel electrophoresis (DGGE) with polymerase chain reaction (PCR) amplified genes is now a well-established technique in environmental microbiology (Muyzer 1999; Torsvik et al. 1998). The most widely used target of PCR-DGGE is the 16S rRNA gene because it is essential to all living prokaryotes and the gene is helpful in tracing phylogenetic relationships by referring to a huge accumulated database (e.g. the Ribosomal Database Project II; http://rdp.cme.msu.edu. The PCR-DGGE of amplified 16S rRNA gene is a useful tool for studying the diversity of bacterial communities in the environment. However, as the 16S rRNA gene is not a direct marker for describing “function”, it can be difficult to connect the changes in DGGE profiles with the population dynamics of a certain functional community of bacteria. Furthermore, the limitation of using 16S rRNA gene PCR has been revealed by applying a metagenomic approach, as new taxa were found after the survey by 16S rRNA gene PCR (Baker et al. 2006). Several new trials on PCR-DGGE targeting amplified “functional genes” (e.g. the ammonium monooxygenase gene, amoA; Oved et al. 2001) may reduce the inaccuracy of the codon usage. A precondition of using a “functional gene” of bacteria for PCR-DGGE is the dependence on developing a specific primer that can be used to amplify genes from a wide diversity. If an ALP gene is investigated using sequence-based separation techniques like PCR-DGGE on the 16S rRNA gene, the tool could provide important information about the ALP-specific genetic potential of the soil bacterial community and its impact on P turnover.

In the present study we investigated ALP activity in the rhizosphere and established analytical techniques for bacterial communities with ALP activity using a PCR-DGGE method with newly designed primers. We examined the phylogenetic relationships of bacterial ALP genes and analyzed bacterial community structure changes with different soil management.

MATERIALS AND METHODS

Study site and field design

The study field was located at the Hokkaido Central Agricultural Experiment Station, Naganuma, Japan (43°3′Ν, 141°45′Ε). The soil type of the field was classified as Andosol. In 2003, an experimental site was established with the following treatments: chemical fertilizer plot (CF), 140 kg N ha⁻¹ year⁻¹, 52.2 kg P ha⁻¹ year⁻¹ and 100 kg K ha⁻¹ year⁻¹ applied as ammonium sulfate, double superphosphate and potassium sulfate, respectively; organic matter plot (OM), 25 Mg of manure (derived from crop residue) per hectare per year, 2 Mg of rice bran per hectare per year and 1,070 kg of fish meal per hectare per year. The same amount of total N, P and K applied in OM by the organic matter was applied to CF by chemical fertilizer. Each treatment was duplicated with plot sizes of 4.5 m × 6.0 m randomly distributed in the field. The present report is based on results obtained in the fourth year (2006). Fertilizer and organic matter were applied to CF and OM, respectively, on 26 May 2006. Seeds of lettuce (Lactuca sativa L. cv. Mizusawa) were sown on 12 May 2006 and transplanted on 6 June 2006 at 44,400 hills per hectare of planting density. Plants were sampled at 32 and 53 days after fertilizer application (DAF) and harvested on 18 July 2006. Plants were dried in an air-forced oven for 2 days at 65°C to obtain dry weight (DW), then ground for further analysis. Soil was sampled just before fertilizer application (BF) and at 11 DAF from the bulk soil, and at 32 and 53 DAF from both the rhizosphere and bulk soil. One composite soil sample consisting of three cores (15 cm of topsoil) was taken per plot, and subsamples were mixed by sieving. One composite rhizosphere sample was taken per plot and consisted of the roots of three randomly selected plants. The roots were shaken vigorously to separate soil not tightly adhering to the roots. The soil samples for gene analysis were stored at –80°C until the extraction of DNA. For soil chemical analysis, samples were passed through a 2-mm sieve and stored at 4°C. The chemical properties of the soils at BF are summarized in Table 1 (Hokkaido Central Agricultural Experiment Station 1992).

Table 1 Chemical properties of the soil (0–15 cm) before fertilization

Treatment	pH (H2O)	Total C (g kg^−1)	Total N (g kg^−1)	Total P (g kg^−1)	Available P (mg kg^−1)	Exchangeable cations (mmolc kg^−1)
						K2O	MgO	CaO
CF	6.4	21	1.9	1.0	76.0	4.9	24	84
OM	6.5	21	1.9	1.1	91.4	4.8	26	87
CF, chemical fertilizer plot; OM, organic matter plot.

Soil ALP activity

The ALP activity was determined using the method described by Tabatabai and Bremner (1969). The soil was incubated in a solution with p-nitrophenyl phosphate (p-NPP) and the formation of p-nitrophenol was measured using a spectrophotometer U-3000 (Hitachi, Tokyo, Japan). The ALP activity was evaluated using a modified universal buffer (MUB) at pH 11.

Soil biomass P and available P

Biomass P (Brookes et al. 1982) was calculated from the amount of inorganic P extracted by 0.5 mol L⁻¹ NaHCO₃ by subtracting the amount of P extracted from non-fumigated soil from the amount of P extracted from moist soil that had been fumigated with CHCl₃ for 24 h. Phosphorus content was determined using the ammonium molybdate–ascorbic acid method (Murphy and Riley 1962). Available P was determined by spectrophotometer (U-3000; Hitachi) using the method described by Truog (1930).

Plant analysis

For the determination of total N and P content in plants, dried samples were digested with 4 mL H₂SO₄ and 300 g L⁻¹ H₂O₂ in a Kjeldahl flask. Nitrogen was determined by spectrophotometer using the Indophenol blue method (Horn and Squire 1966) and P was determined by colorimeter using the vanadomolybdate yellow method (Bertramson 1942).

DNA extraction

Soil DNA extraction was carried out using ISOIL for Beads Beating (Nippon Gene, Tokyo, Japan). The DNA extracts were purified with the Wizard DNA Clean-Up System (Promega, Madison, WI, USA) as recommended by the manufacturer. Purified DNA was stored at –20°C for PCR-DGGE analyses.

Design of the ALP gene primers

We designed primers to amplify partial fragments encoding ALP from soil DNA. The primers were designed based on an alignment of amino acid and nucleotide sequences encoding an ALP gene derived from various isolates: Bacillus subtilis 168 (database accession number AL009126), Nostoc sp. PCC7120 (BA000019), Caulobacter crescentus CB15 (AE005673), Pseudomonas aeruginosa PAO1 (CP000438), Sinorhizobium meliloti 1021 (AL591688), Mesorhizobium loti MAFF303099 (BA000012) and Corynebacterium glutamicum ATCC13032 (BA000036). The set of primers is ALPS-F730 (5′-CAGTGGGACGACCACGAGGT-3′; M. loti position 730–749) and ALPS-R1101 (5′-GAGGCCGATCGGCATGTCG-3′; M. loti position 1083–1101). A GC clamp (5′-CGC CCG CCG CGC CCCGCG CCC GTC CCG CCG CCC CCG CCC G -3′) was attached to the 5′ end of the ALPS-R1101 to improve the separation of the PCR fragments (Myers et al. 1985).

PCR and DGGE

The PCR was carried out with a Thermal Cycler Dice (Takara Bio, Shiga, Japan) using Takara Ex-Taq (Takara Bio). The reaction mixture was prepared with template DNA (approximately 10 ng), 2 µmol L⁻¹ of each primer, 1 × PCR buffer for Ex-Taq (which included 2 mmol L⁻¹ of MgSO₄), 0.2 mmol L⁻¹ of each dNTP, and 0.5 U of Ex-Taq, in a final volume of 20 µL. The thermal cycle profile was as follows: initial denaturation at 94°C for 3 min, 35 cycles of denaturation at 94°C for 1 min, annealing at 57°C for 1 min, extension at 72°C for 2 min, final extension at 72°C for 7 min, and cooling at 4°C.

The DGGE analysis was carried out using a D-Code universal mutation system (Bio-Rad Laboratories, Richmond, CA, USA) according to the instruction manual. The conditions for separation were as follows: running at 90 V for 16 h in a 10% polyacrylamide gel with a denaturing gradient ranging from 40 to 60% at 60°C. After electrophoreses, gels were stained with SYBR Green I nucleic acid gel stain (Molecular Probes, Leiden, The Netherlands) following the manufacturer's instructions, and the bands were visualized with a LumiVisonPRO 400EX (Aishin-Seiki, Nagoya, Japan). Major bands on the gels were excised for sequencing.

Sequencing of DGGE bands

Excised pieces of DGGE gels were washed twice with 1 mL sterilized distilled water in a 1.5 mL tube. A portion of the gel piece (< 1 mm³) was used as the direct template for PCR to recover DNA fragments. The condition for recovering the ALP gene was the same as for the original PCR except that the reverse primer had no GC clamp attached. The PCR products were purified with the MinElute PCR purification kit (Qiagen, Hilden, Germany), ligated into the pGEM-T Vector (Promega) and transformed into ECOS Competent Escherichia coli XL1-Blue (Nippon Gene). The PCR amplification with primers SP6 and T7 was carried out directly on selected white colonies (presumed transformants). Sequencing reactions of selected clones were carried out with a GenomeLab DTCS–Quick Start Kit (Beckman Coulter, Fullerton, CA, USA), with primer T7, 20 µL reaction volume containing 50 fmol DNA template and 2 µmol sequencing primer. Thirty cycles of sequencing reactions (96°C for 20 s, 50°C for 20 s, 60°C for 4 min) were run and the reaction products were analyzed with a CEQ 8000 Genetic Analysis System (Beckman Coulter) after purification by ethanol precipitation.

Phylogenetic analysis

The nucleotide sequences that were determined were evaluated using the BLAST program (Altschul et al. 1997) from the DNA Databank of Japan (DDBJ; Shizuoka, Japan). Sequences were aligned using ClustalW (DDBJ version; http://clustalw.ddbj.nig.ac.jp/top-j.html. Neighbor-joining (NJ) trees (Saitou and Nei 1987) were constructed with ClustalW and drawn using NJplot (Perrière and Gouy 1996; http://pbil.univ-lyon1.fr/software/njplot.html. The sequences generated in the present study have been deposited in the DDBJ database under accession numbers AB306951–AB306969.

Statistical analysis

Soil properties were compared using anova. To characterize the community structure of ALP-harboring bacteria, the values of the DGGE fragments were normalized. Principal component analysis (PCA) and multiple regression analysis were performed using JMP for Macintosh (SAS Institute, Cary, NC, USA).

RESULTS

ALP activity, soil chemical properties and plant analysis

The ALP activity was higher in the rhizosphere soil than in the bulk soil for OM. There was a significant difference in ALP activity between fertilizer application at 32 and 53 DAF (Fig. 1).

Biomass P generally increased with sampling time, and reached a peak at 32 DAF, and decreased thereafter. Although biomass P in OM was generally higher than in CF at 32 and 53 DAF, the difference was not significant (Fig. 2). Regardless of fertilizer application, available P of the rhizosphere tended to be higher than that of bulk soil. There were significant differences in available P between fertilizer application at 32 and 53 DAF (Fig. 3). There was a significant correlation between ALP activity and available P (r = 0.82, P < 0.001). In addition, there were positive correlations between ALP activity and biomass P (r = 0.42, P = 0.042) and between available P and biomass P (r = 0.51, P = 0.012).

Figure 1  Alkaline phosphatase activity in bulk soil (B) and rhizosphere soil (R) in the chemical fertilizer plot (CF) and organic matter plot (OM). Data are mean ± standard error (n = 2). BF, before fertilization; DAF, days after fertilization. Different letters indicate significant differences (P < 0.05).

Figure 2  Biomass P in bulk soil (B) and rhizosphere soil (R) in the chemical fertilizer plot (CF) and organic matter plot (OM). Data are mean ± standard error (n = 2). BF, before fertilization; DAF, days after fertilization. Different letters indicate significant differences (P < 0.05).

Figure 3  Available P in bulk soil (B) and rhizosphere soil (R) in the chemical fertilizer plot (CF) and organic matter plot (OM). Data are mean ± standard error (n = 2). BF, before fertilization; DAF, days after fertilization. Different letters indicate significant differences (P < 0.05).

There were significant differences in DW and P concentration of lettuce between fertilizer applications. However, there was no significant difference in N concentration of lettuce between fertilizer applications (Table 2).

DGGE analysis

The PCR-DGGE profile of the ALP genes is shown in Fig. 4. From the DGGE profile, 19 bands (ALP-1–ALP-19) were excised and sequenced for phylogenetic analyses. Results of a BLAST search based on the deduced amino acid sequences, ALP-1, ALP-6, ALP-9 and ALP-13, showed a high similarity to the ALP of M. loti MAFF303099 (90, 90, 90 and 94% identity, respectively). The closest sequences to ALP-11, ALP-15 and ALP-17 were the ALP of Pseudomonas fluorescens PfO-1 (87, 88 and 81% identity, respectively). ALP-3, ALP-7, ALP-8 and ALP-18 were most closely related to the ALP gene isolated from Anabaena variabilis ATCC29413 (52, 55, 55 and 51% identity, respectively). ALP-2, ALP-5 and ALP-16 showed a similarity to the ALP of Rubrobacter xylanophilus DSM9941 (57, 58 and 61% identity, respectively). The closest sequences to ALP-12 and ALP-19 were the ALP gene isolated from Verminephrobacter eiseniae EF01–2 (55 and 55% identity, respectively). ALP-10 displayed the closest homology to the ALP gene derived from Pseudomonas syringae pv. phaseolicola 1448A (65% identity). ALP-4 was most closely related to the ALP gene derived from Ralstonia metallidurans CH34 (60% identity). And ALP-14 displayed the closest homology to the ALP gene derived from Bradyrhizobium japonicum USDA 110 DNA (56% identity). The NJ tree was drawn based on deduced amino acid sequences of the DGGE bands and related sequences obtained from the DNA data banks using ClustalW (Fig. 5). The result almost reflected the results of BLAST. With regard to the low identity value, another cluster partly showed it, but it was thought that this was based on a difference between the BLAST and ClustalW algorithms.

Table 2 Dry weight and the P and N concentrations of lettuce

	DW (g hill^−1)		P (mg g^−1)		N (mg g^−1)
	32 DAF	53 DAF	32 DAF	53 DAF	32 DAF	53 DAF
CF	5.2 ± 0.9	30.7 ± 4.8	2.9 ± 0.4	4.0 ± 0.2	31.2 ± 0.1	29.9 ± 0.8
OM	7.2 ± 0.6	45.5 ± 4.2	4.0 ± 0.2	4.7 ± 0.2	32.5 ± 0.0	29.4 ± 0.1
t-test	**	*	**	*
*P < 0.05;
**P < 0.1. Data shown are mean ± standard error (n = 2). CF, chemical fertilizer plot; DAF, days after fertilization; DW, dry weight; OM, organic matter plot.

Figure 4  Alkaline phosphatase gene denaturing gradient gel electrophoresis profiles of the bacterial communities using polymerase chain reaction from bulk soil (B) and rhizosphere soil (R) in the chemical fertilizer plot (CF) and organic matter plot (OM). BF, before fertilization; DAF, days after fertilization. Lines are duplicated. M, DGGE Marker II (Nippon Gene, Tokyo, Japan).

Figure 5  Phylogenetic tree based on alkaline phosphatase (ALP) amino acid sequences derived from ALP gene fragments. The tree was produced using a neighbor-joining algorithm. The bar indicates an estimated 10% sequence divergence. Bootstrap values are given for 1,000 replicate trees and values greater than 70% are indicated. The accession number for each sequence is enclosed in parentheses.

The community structures of ALP-harboring bacteria, based on DGGE profiles, were displayed using PCA (Fig. 6). The first two principal components explained 97.5, 89.0, 58.6 and 61.0% of the variance at BF, 11 DAF, 32 DAF and 53 DAF, respectively. Fertilizer treatment significantly affected the community structures of ALP-harboring bacteria at BF and 32 DAF in terms of principal component 1. In addition, when comparing bulk soil and rhizosphere soil in OM or CF, the community structures of ALP-harboring bacteria were significantly different between the rhizosphere and the bulk soil at 32 and 53 DAF in terms of principal component 1. From correlations between the principal component 1 and DGGE band intensity, the principal component 1 was highly influenced by ALP-2 (r = 0.85), ALP-11 (r = 0.82) and ALP-12 (r = –0.82) at 32 DAF, and by ALP-18 (r = –0.90) and ALP-1 (r = –0.88) at 53 DAF. To investigate the influence of community structure on soil ALP activity, the relationship between the ALP activity and the DGGE profiles of ALP-harboring bacteria was evaluated by multiple regression analysis. The ALP activity was used as the dependent variable, and principal components 1 and 2 of the PCA were used as explanatory variables. The multiple regression model at 32 DAF was significant (adj. R ² = 0.81, P = 0.007) and was highly influenced by principal component 1 (principal component 1: P = 0.003, principal component 2: P < 0.175), whereas the model at 53 DAF was not significant (adj. R ² = 0.09, P = 0.338).

DISCUSSION

Effects of organic matter and the rhizosphere on ALP activity

The addition of organic matter to the soil is known to increase the activity of various soil enzymes, such as dehydrogenase, nitrate reductase (Crecchio et al. 2001), β-glucosidase, urease (Madejón et al. 2001) and arginine deaminase (Kandeler et al. 1999). Alkaline phosphatase is also known to be induced by the addition of organic matter to the soil (Lee et al. 2004; Mandal et al. 2007; Yang et al. 2006). In this study, ALP activity in OM plots was higher than in CF plots (Fig. 1). Thus, the activity of ALP-harboring bacteria increased in response to organic matter application. There were also higher ALP activities in the rhizosphere for OM than in the bulk soil (Fig. 1); this result is similar to earlier studies (Kandeler et al. 2002; Tarafdar and Jungk 1987). In the rhizosphere, roots secrete organic compounds, such as sugars, organic acids and polysaccharides, that accumulate and provide energy sources for microbes (Whipps 1990). Thus, increased ALP activity in the rhizosphere for OM suggests that the activity of ALP-harboring bacteria increased because of root exudation even under CF application.

Figure 6  Principal component analysis of denaturing gradient gel electrophoresis profiles of alkaline phosphatase (ALP) bacterial communities. BF, before fertilization; DAF, days after fertilization; B, bulk soil; R, rhizosphere soil. Symbols are the average values of two replicates. The level of variation explained by each principal component is indicated in parentheses. P values are given if there was a significant variety effect determined by anova.

Soil phosphatase activity (including ALP) can be a good indicator of the organic P mineralization potential and biological activity of soils (Chen 2003). There were significant positive correlations between ALP activity and the amount of biomass P, and between ALP activity and available P, suggesting that organic P was converted to biomass P and available P by ALP. In addition, the P concentration of lettuce was higher in OM than in CF (Table 2). This suggests increased mineralization of organic P from organic matter driven by increased microorganism ALP activity and, thus, plants could extract more available P from the rhizosphere. Part of this rhizosphere effect on ALP activity can be explained by significant negative correlations reported between organic P depletion and phosphatase activity in the rhizosphere (Asmar et al. 1995; Tarafdar and Jungk 1987). Furthermore, the contribution of ALP is larger than that of acid phosphatase, although this depends on the soil type (Eivazi and Tabatabai 1977). In the present study, there was a tendency for an increase in available P in the rhizosphere, which is consistent with a higher rate of organic P mineralization than plant P uptake (Tarafdar and Jungk 1987; Fig. 3), indicating that microbial biomass and/or activity may play an essential role in the mineralization of organic P, especially in the rhizosphere. Soil microbial biomass is a major sink and source of plant available P and plays a key role in the biochemical transformation of organic P (Stewart and Tiessen 1987). Active microbial biomass with a high turnover rate can be a slow-release, sustained source of available P (Oberson et al. 2001; Seeling and Zasoski 1993). Biomass P in OM tended to be higher than in CF at 32 and 53 DAF, similar to an earlier study that showed that the microbial biomass P in a manured plot was considerably greater than that in a fertilizer-treated plot (Ghoshal and Singh 1995). There was also a positive correlation between biomass P and available P. These results suggest that the application of organic matter increased ALP activity and biomass P and contributed to the supply of available P in the soil.

Phylogenetic analysis of the DGGE profile

We detected many bands in the DGGE profile of ALP genes regardless of sampling time, fertilizer treatment and sampled soil area (Fig. 4). This is consistent with a report that shows that almost half of all microorganisms in soil and on roots can mineralize organic P via phosphatases (Tarafdar and Claassen 1988). In addition, the sequenced bands in the profiles were homologous to ALP and they were distributed over a wide range on the phylogenetic tree. Annotated results from several sequenced bands show that they are closely related to M. loti and B. japonicum. These free-living rhizobia are known to respond to P stress by increasing ALP (Al-niemi et al. 1997; Smart et al. 1984). Several sequenced bands had a high similarity with P. fluorescens, which is an indigenous bacteria in the soil (Stanier et al. 1966) that is known to generate extracellular ALP (Friedberg and Avigad 1967). Pseudomonas syringae was also annotated in this experiment and is also known to release extracellular ALP (Cheng et al. 1970). As all of the excised bands showed high homology with an alkaline phosphatase gene, these results indicate that the primer set used in the present study had specificity for amplifying ALP genes from soil. This is the first report to apply PCR-DGGE analysis to ALP genes in environmental samples. As the designed primer is based on a limited number of species, further verification of the primer set will be necessary in future. However, it is suitable to monitor bacterial communities containing ALP-harboring bacteria, and for discovering new ALP genes in natural environments.

Community structures of ALP-harboring bacteria

Organic matter is reported to alter bacterial communities (Marschner et al. 2003; Sun et al. 2004); however, there are few reports about specific functions in bacterial communities. The PCA of the ALP gene DGGE profiles indicated that community structures were affected by fertilizer type (Fig. 6). The fertilizer treatment significantly affected bacterial community structures harboring ALP genes at 32 DAF. There were significant differences in ALP activity between CF and OM at 32 DAF, and it is possible that the community structures were involved. The community structures of ALP-producing bacteria were significantly different between the rhizosphere and the bulk soil at 32 and 53 DAF, whereas a significant difference in ALP activity was recognized only in the OM treatment between rhizosphere and bulk soil areas at both sampling times. Decreasing activity of ALP with increasing distance from the root surface may be associated with changes in bacterial community structure (Kandeler et al. 2002), and microbial communities in the rhizosphere are affected by root exudates (Dunfield and Germida 2003; Tesfaye et al. 2003). Thus, the present results also suggest a relationship between the type of fertilizer and root exudates. Further research is underway to determine whether the OM treatment changes the composition and/or quantity of root exudates. As the DGGE bands contributing to principal component 1 in 32 DAF were different from 53 DAF, it is suggested that major bacteria harboring an ALP gene changed with sampling time.

Changes in overall microbial community structure can be correlated with changes in certain functions (Avrahami et al. 2003; Kandeler et al. 2002), and Marschner et al. (2003, 2005) reported that bacterial community structure was correlated with ALP activity in the field. The link between microbial community structure and function is often weak because many ecosystem functions are carried out by a wide range of microbes that form substrate guilds (Zak et al. 1994). Multiple regression analysis between ALP activity and the PCA analysis of ALP gene DGGE profiles suggest that ALP activity is significantly explained by principal component 1 at 32 DAF, which contains the majority of the variance in the community structure. This raises the possibility that different ALP-harboring bacteria release different amounts and/or activities of ALP, and that the structure of ALP-harboring bacterial communities may play a major role in determining soil ALP activity. At 32 DAF, ALP activity and biomass P were at maximum values, indicating that microbial activity was also at a maximum.

This study showed that organic matter application had a major impact on ALP activity and the structure of ALP-harboring bacterial communities. The ALP-harboring bacterial community structure was in part significantly correlated with ALP activity. Further research on the characterization of the community structure will help explain the change in ALP activity.

ACKNOWLEDGMENTS

This research has been partly supported by a grant from the Northern Advancement Center for Science and Technology (NOASTEC Foundation).