Evaluation of soil storage methods for soil microbial community using genetic and metabolic fingerprintings

European Journal of Soil Biology 63 (2014) 55e63

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European Journal of Soil Biology journal homepage: http://www.elsevier.com/locate/ejsobi

Original article

Evaluation of soil storage methods for soil microbial community using genetic and metabolic fingerprintings Hang Cui a, Caihuan Wang a, Zhenhong Gu a, b, Honghui Zhu b, Shenlei Fu c, Qing Yao a, * a

South China Agricultural University, College of Horticulture, Wushan St. 483, Tianhe Dist., Guanghzou 510642, PR China Guangdong Institute of Microbiology, Guangzhou 510070, PR China c Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Science, Guangzhou 510160, PR China b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 5 December 2013 Received in revised form 17 May 2014 Accepted 30 May 2014 Available online 11 June 2014

Soil microbes are essential functional components in soil ecosystems, involved in diverse biogeochemical processes. Storage of soil samples for soil microbial community analysis is sometimes inevitable because of large quantity of samples. The effects of storage on soil microbial community, however, is less revealed, especially using denaturing gradient gel electrophoresis (DGGE) and community level physiological profiling (CLPP), the most widely used techniques for microbial ecology. We stored forest land (FL) soils and arable land (AL) soils at 4
C after air drying (AirDrying) or at 20
C with field moisture (Freezing) for two month, and then the microbial community structures and metabolic activities in the stored soils were compared to those in the fresh soils, using PCR-DGGE profiling and Biolog® microplate. Similarity coefficients indicate that both storage methods shifted microbial community structure depending on soil types and microbial types. Microbial community in AL soils is more stable than that in FL soils, and fungal community is more stable than bacterial community. Freezing changed microbial community less than AirDrying based on genetic fingerprinting, however, microbial metabolic activity was greatly decreased by both storage methods. Our results suggest that, fresh soils are the best choice if microbial metabolic activity is under investigation while freezing at 20
C for less than two months is acceptable if microbial community is studied on the basis of genetic fingerprinting. © 2014 Elsevier Masson SAS. All rights reserved.

Keywords: CLPP DGGE Microbial community Metabolic activity Soil microbe Storage methods

1. Introduction Soil microbes are essential biological components in soil ecosystems, undertaking diverse biogeochemical processes for soil functioning. In the study on soil microbes, the microbial diversity and metabolic activity are commonly the most attractive [1,2] because they reveal some fundamental principles in the field of microbial ecology. For example, recent work indicated that loss in soil microbial diversity significantly decreased the potential denitrification activity in soil of up to 4e5 folds [3]. Undoubtedly, fresh soils immediately after sampling are ideal material for the investigation of both microbial diversity and metabolic activity [4e7], however, this is sometimes impossible due to large amount of samples or comparison among chronological samples. In these cases, storage of soils is necessary.

* Corresponding author. E-mail address: [email protected] (Q. Yao). http://dx.doi.org/10.1016/j.ejsobi.2014.05.006 1164-5563/© 2014 Elsevier Masson SAS. All rights reserved.

Several storage conditions have been practiced for this purpose, such as storage at 4
C after air drying, storage at 20
C at field moisture. The effect of storage on microbial community and metabolic activity has also been assessed. However, results are not consistent among studies. Peoples and Koide [8] evaluated the impacts of the storage of soil samples on enzyme activity (1,4-bcellobiohydrolase, acid phosphatase and b-N-acetylglucosaminidase) and found the enzyme activities decreased due to freezing and drying. Trabue et al. [9] indicated that storage of soils at 4
C for 3 or 6 months not only reduced the soil microbial biomass and community structure [evidenced by phospholipid fatty acid (PLFA) analysis] but also decreased the microbial function and metabolic pathway (evidenced by the degradation of metsulfuron-methyl). Compared with fresh soils, drying and rewetting significantly reduced microbial biomass, respiration, most enzyme activities, total DNA, and total fatty acid methyl esters (FAME) concentrations in soils [10]. Lee et al. [10] concluded that storage should be avoided whenever possible, particularly for extraction of FAME and total DNA, but that 4
C or 20
C is the best storage method for FAME analysis, and 80
C is preferable for DNA analysis. Based on PLFA

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analysis, total PLFA concentrations decreased by more than 28% following storage of the freeze-dried soils for 1 year at 70
C, and the PLFA profiles also changed during storage over this period, suggesting that PLFA analyses are best done as soon as possible after sampling [11]. When most researches demonstrate that storage can greatly affect microbial community structure and reduce microbial metabolic activity, some studies indicate that storage does not affect these properties or even increase enzyme activities. Pesaro et al. [12] found that degradation of the methidathion (a crop protection product) appeared unaffected in the soils frozen at 20
C for 4 days, although soil DNA content and direct cell counts were decreased. Luo et al. [13] reported that storage of airdried soils for up to seven weeks increased the denitrification activity in pasture soils. It is surprising that almost all research focused on bacterial community, with little information on fungal community, although the role of soil fungi is fundamental to the soil ecosystems [14]. To evaluate the effect of storage on soil microbial diversity, culture-independent techniques have normally been applied, including FAME [10], PLFA, barcoded pyrosequencing of bacterial 16S rRNA genes and length heterogeneity PCR [6,11,15,16]. For soil microbial metabolic activity, soil respiration, activities of specific enzymes and even degradation of substrates have been used as indicators. During the past two decades, a powerful molecular tool for microbial ecology, denaturing gradient gel electrophoresis (DGGE), has been developed [17], and successfully applied in diverse environmental samples [18e21]. Almost at the same time, the technique of community level physiological profile (CLPP) using Biolog® microplate appeared and has also been widely accepted and applied to study on microbial metabolic activity of environmental samples [22e27]. Despite of their popularity, the study on the effect of storage on microbial community using these two techniques is very scarce, and consequently, the results of the research on soil microbial community using these two techniques are subjected to reassessment. The objective of this study was to evaluate the effect of two soil storage methods (e.g. storage at 4
C following air drying and storage at 20
C at field moisture) on the microbial community structure and metabolic activity using PCR-DGGE and Biolog® microplate techniques. For this purpose, two representative soils (forest land soils and arable land soils) were sampled and both bacterial and fungal communities were assessed.

2. Material and methods 2.1. Soil samples and storage conditions Forest soils and agricultural soils are two types of important soil ecosystems and they are always the targets of soil microbiologist. Consequently, we chosen forest soils and arable soils as samples in this study. Soil samples were collected from a forest area and a vegetable plot at Heshan Hilly Land Interdisciplinary Experimental Station, CAS (E112
540 , N22
410 ), representative of forest land (FL) soils and arable land (AL) soils respectively. Soil properties of FL and AL soils are shown in Table 1. Climate and soil type in this area are as reported previously [28]. For FL soil collection, four sites at the same contour line were chosen about 30 m apart from each other. At each site, six soil core of 20 cm deep were sampled, homogenized and sieved (2 mm pore size), and the composite sample was immediately transported to the laboratory on ice in a refrigerating box within 1 h. For AL soil collection, four raised beds in the vegetable plot were chosen about 10 m apart from each other and six soil cores were taken on each bed. AL soils were treated as for FL soils.

Table 1 Chemical properties of forest land soils and arable land soils. Values are the mean ± standard error of four replicates. Chemical property

Forest land soil

pH(H2O) SOM content (g kg1) Total N (g kg1) Total P (g kg1) Total K (g kg1) Available N (mg kg1) Available P (mg kg1) Available K (mg kg1)

4.68 31.0 1.11 0.19 13.40 68.45 1.42 29.97

± ± ± ± ± ± ± ±

0.15 2.7 0.09 0.01 1.24 5.92 0.41 1.03

Arable land soil 5.60 15.2 0.60 0.78 8.97 40.03 120.01 138.32

± ± ± ± ± ± ± ±

0.03 0.5 0.02 0.05 0.09 1.49 11.19 13.43

In contrast to fresh soils (Fresh), soil samples were subjected to two storage conditions, namely storage at 4
C after air drying for two months (AirDry) and freezing at 20
C with field moisture for two months (Freeze). 2.2. Extraction of total soil DNA Total soil DNA was extracted using PowerSoil® DNA Isolation Kit (MO BIO Laboratories Inc.) according to manufacturer protocol. For fresh soils, DNA was extracted immediately after soils were transported to lab and the extracted DNA was stored at 20
C for later analysis. For stored soils, DNA was extracted after storage for two months. When DNA from all soils was extracted, they were subjected to PCR-DGGE for microbial community structure analysis. 2.3. PCR-DGGE To investigate the genetic diversity of soil microbes, the V3 region of bacterial 16S rRNA and fungal 18S rRNA were amplified. For bacterial 16S rRNA, nested PCR was conducted with 27F/1492R and GC-341F/518R as the first and second primer set, respectively [17,29]. For fungal 18S rRNA, primer set N31/GC-fung was applied followed by a “reconditioning PCR” to eliminate the possible formation of heteroduplexes [30e32]. PCR products were checked for correct size by electrophoresis on a 2% agarose gel stained with Gold view (SBS Genetech Inc., China) before DGGE analysis. DGGE analysis was conducted with a D-Code Universal Mutation Detection System (Bio-Rad Laboratories). For bacterial 16S rRNA genes, DGGE fingerprints were run on a 8% polyacrylamide gel for 15 h at a constant voltage of 70 V and at 60
C in a 45%e70% horizontal denaturant gradient (the 100% denaturant agent used included 7 M urea and 40% deionized formamide). For fungal 18S rRNA genes, DGGE fingerprints were run on a 6% polyacrylamide gel for 15 h at a constant voltage of 70 V and at 60
C in a 25%e35% horizontal denaturant gradient (the 100% denaturant agent used included 7 M urea and 40% deionized formamide). Gels were photographed with UV transillumination after SYBR® GOLD staining for 30 min [33]. 2.4. Biolog® microplate analysis To investigate the metabolic activity of soil microbes, Biolog® microplate analysis was conducted using Biolog® EcoPlate™ according to previous studies [22,23]. Briefly, soils (equal to 10 g dry soils) were added with 100 ml sterile 0.85% NaCl solution in a 250 ml flask, shaked at 180 rpm for 20 min, and then incubated on ice for 5 min. Five ml soil suspension was taken and eluted 10-fold by adding with 45 ml 0.85% NaCl solution, and this elution was repeated two times until the soil suspension was eluted 1000-fold. 150 ml of the final elution containing soil microbial community was added to each well of Biolog® microplate, and then incubated at

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30
C. During the incubation period of 9 days, the absorbance value at 590 nm was recorded using an automatic microplate reader (Tecan Infinite M200) at regular 24 h intervals. Microbial metabolic activity in each microplate was quantified as average well-color development (AWCD) as follows: AWCD ¼ SODi/31, where ODi is the optical density value from each well [34]. Richness (R) was calculated using an OD of 0.25 as threshold for positive response [23]. ShannoneWeaver diversity index (H) was calculated as follows: H ¼ SPi(ln Pi), where Pi is the ratio of the activity on each substrate (ODi) to the sum of activities on all substrates (SODi) [34].

57

quantified by calculating the Sorensen pairwise similarity coefficient (Cs) [37]. IBM SPSS statistics software version 21 (SPSS Inc., Chicago, IL) was used to perform analysis of variance (ANOVA), principle component analysis (PCA) and cluster analysis (CA). For DGGEbased genetic fingerprinting, PCA and CA were conducted according to the presence (1) or absence (0) of the particular band. For Biolog® microplate-based metabolic fingerprinting, PCA and CA were conducted according to the absorbance values of 31 wells containing difference carbon sources at 72 h of incubation [23]. All the results presented in the study represent the mean values of four replicates.

2.5. Data analysis and statistics 3. Results For DGGE-based microbial community analysis, Quantity One (Bio-Rad Laboratories Inc.) and Bio-Dap (http://nhsbig.inhs.uiuc.e du/wes/populations.html) software were employed to calculate the ShannoneWeaver diversity index (H) and species evenness (E) [35], while species richness (R) was recorded as the number of DGGE bands of each sample [36]. To compare the changing effects of two storage methods on microbial community, similarity between fresh soils and stored soils on the basis of DGGE profiling was

3.1. Effects on microbial community based on genetic fingerprinting DGGE profiles (Fig. 1) indicated that both AirDrying and Freezing changed the microbial community structures and the effects on bacterial community and fungal community were different from each other. A total of 29 and 29 bands were detected for bacterial and fungal community in forest land soil, and 28 and 23 bands in

Fig. 1. DGGE profiles of bacterial 16S rRNA and fungal 18S rRNA of microbial community in fresh soils and stored soils. Fresh, fresh soils; AirDry, stored soils at 4
C after air drying; Freeze, frozen soils at 20
C at field moisture.

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Fig. 2. DGGE band abundance as affected by storage methods. Open bars indicate fresh soil; gray bars indicate soil stored at 4
C after air drying; black bars indicate soil frozen at 20
C at field moisture. *, ** and *** indicate a significant difference at P ¼ 0.05, 0.01 and 0.001 levels, respectively, between the fresh soil and each of the stored soils (t test).

arable land soil. According the abundance, 16 (55.2%) bacterial and 11 (39.7%) fungal populations in forest land soil were significantly affected by AirDrying and/or Freezing, while 14 (50.0%) and 10 (43.5%) in arable land soil were affected (Fig. 2). It seems that fungal community was more stable than bacterial community. More interestingly, some populations in a particular soil were increased while others were decreased by a particular storage method, indicating different responses of microbial populations to storage. According to quantitative analysis (Table 2), freezing significantly increased bacterial diversity and air drying significantly decreased fungal diversity in FL soils. In contrast, however, they did not affect the microbial diversity in AL soils. Species richness was

Table 2 ShannoneWeaver diversity index (H), species richness (R) and species evenness (E) of the microbial community as affected by storage methods. Data is derived from the DGGE profiles. Values are the mean ± standard error of four replicates. Values followed by the same letter are not significantly different at the 5% level (Duncan's multiple range test) within a column for each soil type. Fresh, fresh soils; AirDrying, stored soils at 4
C after air drying; Freezing, frozen soils at 20
C at field moisture. Soil type

Storage method

Forest land soil

Fresh AirDrying Freezing Fresh AirDrying Freezing

Arable land soil

Forest land soil

Arable land soil

Forest land soil

Arable land soil

Fresh AirDrying Freezing Fresh AirDrying Freezing Fresh AirDrying Freezing Fresh AirDrying Freezing

Bacteria H 1.86 1.96 2.18 2.38 2.51 2.38 R 21.2 23.3 24.8 21.3 22.3 20.3 E 0.61 0.62 0.66 0.77 0.81 0.79

not changed except that air drying significantly decreased it for fungal community in AL soils. Species evenness was not affected for bacterial community, but air drying significantly decreased it for fungal community in FL soils and freezing significantly increased it for fungal community in AL soils (Table 2). These data suggests the complexity of the effects of storage on microbial community depending on soil types and microbial types. Cs between fresh soils and stored soils varied between 0.67 and 0.84 (Table 3) indicating the changing effects of storage on microbial community. Similar to data in Table 2, this effect was significantly associated with soil types (P ¼ 0.002) and microbial types (P ¼ 0.000). In detail, the change in microbial community by storage in AL soils (higher average Cs) was less than that in FL soils (lower average Cs), and the change by storage in fungal community (higher average Cs) was less than that in bacterial community (lower Cs average) (Table 3). However, no significant difference was observed between the two storage methods (P ¼ 0.587), indicating that both storage methods affected the microbial community at the same degree. Principle component analysis and cluster analysis were used to compare the difference in the effect of the two storage methods

Fungi

± ± ± ± ± ±

0.07 0.07 0.11 0.10 0.09 0.08

± ± ± ± ± ±

1.9 2.7 2.1 0.8 0.9 1.2

± ± ± ± ± ±

0.02 0.04 0.03 0.08 0.05 0.05

b ab a a a a

a a a a a a a a a a a a

3.02 2.73 2.92 2.44 2.55 2.46

± ± ± ± ± ±

0.12 0.07 0.13 0.09 0.07 0.05

27.8 28.1 28.8 20.2 17.8 18.8

± ± ± ± ± ±

2.0 2.3 1.5 1.0 0.7 1.1

0.90 0.82 0.88 0.82 0.89 0.86

± ± ± ± ± ±

0.04 0.02 0.05 0.01 0.03 0.05

a b ab a a a

a a a a b ab a b ab b a ab

Table 3 The Sorensen's pairwise similarity coefficient (Cs) between the stored soils and the fresh soils based on the DGGE profiles. Values are the mean ± standard error of four replicates. AirDrying, stored soils at 4
C after air drying; Freezing, frozen soils at 20
C at field moisture. Soil type Forest land soil

Storage method

AirDrying Freezing Arable land soil AirDrying Freezing Three-way ANOVA (P value) Soil type (ST) Microbial type (MT) Storage method (SM) ST  MT ST  SM MT  SM ST  MT  SM

Bacteria 0.67 0.71 0.74 0.72

± ± ± ±

0.002 0.000 0.587 0.924 0.995 0.815 0.020

0.02 0.01 0.02 0.01

Fungi 0.78 0.76 0.80 0.84

± ± ± ±

0.01 0.03 0.02 0.02

H. Cui et al. / European Journal of Soil Biology 63 (2014) 55e63

(Fig. 3). In FL soils, bacterial community in frozen soils was closer to that in fresh soils (Fig. 3-A, B) while it was unclear for fungal community (Fig. 3-C, D). In AL soils, the effects of two storage methods on bacterial community were comparable (Fig. 3-E, F)

59

while fungal community in frozen soils seemed closer to that in fresh soils (Fig. 3-G, H). Taking together, these data implied that AirDrying changed the microbial community greater than Freezing.

Fig. 3. Principle component analysis and cluster analysis of microbial community in fresh soils and stored soils based on DGGE profiles of bacterial 16S rRNA and fungal 18S rRNA. Fresh, fresh soils; AirDry, stored soils at 4
C after air drying; Freeze, frozen soils at 20
C at field moisture. A and B, bacteria in forest land soils; C and D, fungi in forest land soils; E and F, bacteria in arable land soils; G and H, fungi in arable land soils.

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3.2. Effects on metabolic activity based on CLPPs Results in Fig. 4 showed that AWCD values gradually increased during the incubation period of 9 days, and soil storage greatly decreased the microbial metabolic activity. At 3 days of incubation, Freezing and AirDrying decreased AWCD by 52.3% and 60.9% for FL soils with significant difference between two storages (P ¼ 0.009) and by 57.8% and 62.5% for AL soils without significant difference (P ¼ 0.631), respectively. Thus, at least for FL soils, the lower AWCD values for air dried soils than for frozen soils indicated a more negative effect of AirDrying on metabolic activity than Freezing. Taking the AWCD values at 3 days after incubation for community analysis, it is clear that storage methods significantly decreased species richness (P ¼ 0.000) and ShannoneWeaver diversity (P ¼ 0.000), while soil types only affected species richness (P ¼ 0.005) (Table 4). When two storage methods were compared, AirDrying showed more inhibitory effect than Freezing, but the effect was significant only for ShannoneWeaver diversity in AL soils (Table 4). Principle component analysis and cluster analysis of AWCD value at 3 days after incubation did not differentiate two storage methods and both of them were far apart from fresh air (Fig. 5). This is much different from the results from DGGE profiling. The 31 carbon sources in Biolog® microplate include six guilds: polymers, carbohydrates, carboxylic acids, amino acids, amines and phenolic compounds. Data in Table 5 indicated that soil type did not affect the metabolic activity of all six microbial groups, however, soil storage significantly decreased the metabolic activity of microbial groups utilizing polymers, carbohydrates, amino acids and

Fig. 4. Average well color development (AWCD) values of microbial community at 30
C using Biolog® EcoPlate™. AWCD value is calculated according to the absorbance at 590 nm recorded at regular 24 h intervals. Error bar represents one standard error. Dn indicates n days after incubation. Fresh, fresh soils; AirDry, stored soils at 4
C after air drying; Freeze, frozen soils at 20
C at field moisture.

Table 4 ShannoneWeaver index (H) and species richness (R) based on community level physiological profiles detected using Biolog® EcoPlate™. Values are the mean ± standard error of four replicates. Values followed by the same letter are not significantly different at the 5% level (Duncan's multiple range test) within a column for each soil type. Fresh, fresh soils; AirDrying, stored soils at 4
C after air drying; Freezing, frozen soils at 20
C at field moisture. Soil type Forest land soil

Storage method

Fresh AirDrying Freezing Arable land soil Fresh AirDrying Freezing Two-way ANOVA (P value) Soil type (ST) Storage method (SM) ST  SM

H 3.10 2.52 2.60 3.13 2.53 2.63

R ± ± ± ± ± ±

0.344 0.000 0.907

0.21 0.16 0.19 0.19 0.03 0.05

a b b a c b

23.5 ± 1.0 a 9.3 ± 0.8 b 10.0 ± 0.7 b 25.8 ± 2.1 a 10.3 ± 0.9 b 11.8 ± 1.2 b 0.005 0.000 0.629

amines. The effect of AirDrying and Freezing was almost the same, except that the inhibitory effect of AirDrying on amine-utilizing microbial group was greater than Freezing (Table 5). 4. Discussion Using DGGE profiling, a widely used genetic fingerprinting technique, we demonstrated that both of the storage methods analyzed, AirDrying and Freezing, affected microbial community structure (Fig. 1, Tables 2 and 3). This alteration of microbial community structure due to air drying or freezing has been revealed with PFLA analysis previously [15]. These authors argued that the changes in both total PFLA content and PFLA profiles may be caused by cell death in response to high energy requirement when the temperature changes. However, our result is contrary to the other DGGE-based research [7] where air drying and freezing did not change the microbial community stored for one year. In our study, soil total DNA was extracted for PCR-DGGE profiling. Since soil DNA extraction procedure was consistent for all three soils, DNA degradation may explain the difference. Stres et al. [38] reported that 10 cycles of freeze/thaw at 4
C/4
C slightly decreased DNA recovery from soils while the following incubation at 4
C greatly decreased it. This result suggests that freezing at 20
C and storage at 4
C after air drying in our study may have promoted the DNA degradation and induced the difference in microbial community structure between fresh soils and stored soils. In contrast, a few studies using other DNA-based genetic techniques, such as barcoded pyrosequencing [16] and length heterogeneity PCR [6], demonstrated that freezing or air drying storage did not significantly influence the microbial community. This inconsistency might be the difference in storage period or assessment method. For example, soils were stored for only 14 days [16] in contrast to 60 days in our study, and similarity analysis was applied to assess the storage effect [6] in contrast to the diversity parameters (H, R, E) in our study. Interestingly, soil storage did not affect the microbial community in our study if similarity analysis was applied, the same to previous study [6]. Additionally, in our study, it is interesting that the alteration in microbial community structure due to storage strongly depended on microbial types and soil types, e.g. ShannoneWeaver diversity index was changed for FL soils but not for AL soils, and species evenness was changed for fungi but not for bacteria. Soil DNA pool consists of both intracellular and extracellular fraction [39], with the latter representing a significant portion of the entire soil metagenome [40]. In this study, when two storage methods were compared, it is clear that the changing effects of AirDrying and Freezing were comparable (see Cs values in Table 3

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Fig. 5. Principle component analysis and cluster analysis of microbial community in fresh soils and stored soils based on community level physiological profiling at 3 days after incubation using Biolog® EcoPlate™. Fresh, fresh soils; AirDry, stored soils at 4
C after air drying; Freeze, frozen soils at 20
C at field moisture. A and B, forest land soils; C and D, arable land soils.

and grouping patterns in Fig. 3), because both storage conditions can promote the degradation of soil DNA [38,41]. We found that fungal community was less affected than bacterial community according to Cs values. This can be well explained by the fact that bacterial DNA is more easily exposed to soil environments than fungal DNA, because the turnover times of soil fungi are up to one order of magnitude greater than those of soil bacteria [42]. We also found that microbial community structure in AL soils was less affected than that in FL soils according to Cs values, which may be attributed to the difference in chemical properties of two soil types in our study. Levy-Booth et al. [41] concluded that the DNA absorption to soil matrix and DNA binding capacity of soil is influenced by an interaction between soil pH, cation concentration, and soil texture. DNA absorption and DNA binding represent protection from degradation by DNase [43]. In our study, pH values of forest land and arable land greatly differed (4.68 vs. 5.60). These huge

differences may affect the DNA absorption and binding and further lead to different degradation rate of DNA during storage. Additionally, the soil pH change up to 0.55 units induced by air drying storage has been reported [44]. We did not measure the soil pH change after storage, however, the change is predictable. Using Biolog® EcoPlate™, a popular CLPP technique, we demonstrate that storage can be inhibitory to microbial metabolic activity (Fig. 4). Up to date, very few studies on this aspect [45,46] ~ ones have been conducted using CLPP technique. Gonzalez-Quin et al. [46] indicated that storage shifted CLPP profile at 3e24 days of storage time depending on soil types, however, no information on AWCD was available therein. When literature with CLPP is scarce, most research assess the effect of storage methods on microbial metabolic activity using enzyme activity assay [5,8,10,47,48] or microbial function assessment [4,49,50]. With 1,4-b-cellobiohydrolase, acid phosphatase and b-N-acetylglucosaminidase as

Table 5 Growth responses of different microbial groups to storage methods as revealed by AWCD values based on community level physiological profiles detected using Biolog® EcoPlate™. Values are the mean ± standard error. Values followed by the same letter are not significantly different at the 5% level (Duncan's multiple range test) within a column for each soil type. Fresh, fresh soils; AirDrying, stored soils at 4
C after air drying; Freezing, frozen soils at 20
C at field moisture. Soil type Forest land soil

Storage method

Fresh AirDrying Freezing Arable land soil Fresh AirDrying Freezing Two-way ANOVA (P value) Soil type (ST) Storage method (SM) ST  SM

Polymers 0.478 0.083 0.115 0.613 0.078 0.175 0.285 0.000 0.627

± ± ± ± ± ±

0.115 0.025 0.031 0.115 0.017 0.052

Carbohydrates a b b a b b

0.887 0.180 0.230 1.112 0.268 0.274 0.068 0.000 0.494

± ± ± ± ± ±

0.101 0.043 0.049 0.130 0.053 0.062

a b b a b b

Carboxylic acids 0.684 0.500 0.591 0.766 0.613 0.662 0.335 0.329 0.981

± ± ± ± ± ±

0.110 0.093 0.114 0.104 0.130 0.110

a a a a a a

Amino acids 0.577 0.151 0.209 0.687 0.221 0.222 0.273 0.000 0.797

± ± ± ± ± ±

0.070 0.054 0.072 0.074 0.077 0.078

Amines a b b a b b

0.327 0.077 0.114 0.323 0.034 0.112 0.478 0.000 0.714

± ± ± ± ± ±

Phenolic compounds 0.024 0.024 0.043 0.035 0.011 0.020

a b b a c b

0.388 0.187 0.233 0.497 0.286 0.390 0.165 0.154 0.958

± ± ± ± ± ±

0.066 0.078 0.096 0.084 0.121 0.160

a a a a a a

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targets, Peoples and Koide [8] indicated the inhibitory effect of freezing and drying on microbial metabolic activity. Mortensen and Jacobsen [4] took the degradation of herbicide as indicator of microbial function and found that storage of soils at 20
C resulted in substantial increase in the 50% disappearance time of metribuzin from <15 days to 36 days when compared to fresh soils. Although overall enzyme activity in soils may be of plant or microbial origin, it can reflect the soil microbial function to a great degree. Together with our results, these data suggest a strong negative effect of storage, regardless of storage methods, on soil microbial metabolic activity. However, it is worthy to note that not all microbial groups was inhibited, for example, the metabolic activity of carboxylic acid- and phenolic compound-utilizing microbial groups was not affected by soil storage. Additionally, some cautions should be taken to interpret the change in microbial community revealed using Biolog® microplates, because the microbial community has a chance to change as a consequence of growth of some populations over a long incubation time. According to the manufacturer manual, the incubation time of 3 days is appropriate. When storage methods are compared, Freezing seems less inhibitory than AirDrying in our study (Fig. 4), although they were closely grouped using principle component analysis and clustered apart from the fresh soil samples (Fig. 5). Similarly, using enzyme activity as indicator, Abellan et al. [48] demonstrated the influence of several storage methods in the following order: freezing at 20
C > cold storage at 4
C > air drying. However, DeForest [5] showed that enzyme activity of soil stored at 4
C was not significantly different from soil stored at 20
C. These inconsistent results among literature may result from the difference in enzymes under investigation, which was demonstrated by DeForest [5]. He found that the activities of N-acetyl-glucosaminidase, phosphatase, and phenol oxidase appeared sensitive to storage, while b-glucosidase, b-xylosidase, and peroxidase were insensitive. More systematically, Dadenko et al. [51] indicated that the soil storage caused significant changes in the enzyme activities, depending on the soil type, the land use, the type of enzyme, and the duration and conditions of storage. It is interesting that the effect of storage on genetic diversity (revealed by DGGE profiles) depends on soil types and microbial types (Table 3), however, the effect on metabolic diversity (revealed by Biolog® microplate profiles) is constantly inhibitory (Table 4). This reflects the higher sensitivity of soil microbial enzymes to storage than soil microbial genetic material. In conclusion, using PCR-DGGE and Biolog® microplate techniques, we demonstrate that both, freezing soils at 20
C for two months and keeping soils at 4
C after air drying for two months, can shift microbial community structure. The effect depends on microbial type and soil type, where fungal community and arable land soil are more stable than bacterial community and forest land soil that suffer greater changes in their microbial community structure. Storage also greatly decreased the microbial metabolic activity as revealed by AWCD, with air drying been more inhibitory than freezing. Therefore, we suggest that storage be avoided if metabolic activity (such as enzyme activity assay and microbial function assay) is under investigation, while freezing at 20
C for <2 months is acceptable for soil storage if assessment on microbial community based on genetic fingerprinting is of interest. Acknowledgement The authors are sincerely grateful to the two anonymous reviewers for their constructive suggestion on data analysis and language polishing. This study was financially supported by the NSFC-Guangdong Joint Project (U1131001).

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