Microbes Environ. Vol. 26, No. 4, 325–331, 2011 http://wwwsoc.nii.ac.jp/jsme2/ doi:10.1264/jsme2.ME11114

Molecular Characterization of Soil Bacterial Community in a Perhumid, Low Mountain Forest

YU-TE LIN1, WILLIAM B. WHITMAN2, DAVID C. COLEMAN3, and CHIH-YU CHIU1* 1Biodiversity Research Center, Academia Sinica, Nankang, Taipei 11529, Taiwan; 2Department of Microbiology, University of Georgia, Athens, GA, 30602–2605, USA; and 3Odum School of Ecology, University of Georgia, Athens, GA, 30602–2602, USA (Received February 10, 2011—Accepted June 3, 2011—Published online July 5, 2011)

Forest disturbance often results in changes in soil properties and microbial communities. In the present study, we characterized a soil bacterial community subjected to disturbance using 16S rRNA gene clone libraries. The community was from a disturbed broad-leaved, low mountain forest ecosystem at Huoshaoliao (HSL) located in northern Taiwan. This locality receives more than 4,000 mm annual precipitation, one of the highest precipitations in Taiwan. Based on the Shannon diversity index, Chao1 estimator, richness and rarefaction curve analysis, the bacterial community in HSL forest soils was more diverse than those previously investigated in natural and disturbed forest soils with colder or less humid weather conditions. Analysis of molecular variance also revealed that the bacterial community in disturbed soils significantly differed from natural forest soils. Most of the abundant operational taxonomic units (OTUs) in the disturbed soil community at HSL were less abundant or absent in other soils. The disturbances influenced the composition of bacterial communities in natural and disturbed forests and increased the diversity of the disturbed forest soil community. Furthermore, the warmer and humid weather conditions could also increase community diversity in HSL soils. Key words: bacterial community, subtropical forest soils, 16S rRNA genes

Human activities in forestry management result in soil higher temperature and less precipitation (31, 32). Thus, low disturbance. Such disturbances alter the characteristics of soil bacterial diversity could be due to either the lower temperature quality, including soil organic matter content, and result in or higher precipitation. To decide which factor might be quantitative and qualitative changes in soil carbon and important, forest soils with similar precipitation and warmer nitrogen pools, as well as soil biological properties (7–9). climate conditions were investigated. The effects of such disturbance on soil microbial community We examined the diversity and composition of indigenous structure, diversity, and biomass have received some attention soil bacterial communities in a low mountain forest located (12, 16, 39). On the other hand, climate conditions play a at Huoshaoliao (HSL) in northern Taiwan. This region is a critical role in the vegetation type and the accompanying secondary broad-leaved forest and receives >4,000 mm ecosystem. Soil microbial activity and the community annual precipitation, one of the highest precipitations in structure also respond to alterations in climate conditions, Taiwan. Libraries of 16S rRNA genes were prepared from e.g., temperature and rainfall patterns (44, 45). these soils to elucidate the bacterial community. These Previously, we found that the proportion of Proteobacteria libraries provide unequivocal identification of soil organisms accounted for more than 50% of the soil bacterial community (28) and facilitate the analysis of the composition of the soil in pristine perhumid (receiving near 4,000 mm annual bacterial community and comparisons with the communities precipitation) forests in the Yuanyang Lake (YYL) ecosystem from other soils. Considering the disturbances inherent in at relatively high elevation of around 1,800 m (31). In forests tree harvesting and climate conditions, we assumed that the in the vicinity of the same area, harvesting methods affected composition and diversity of the soil bacterial community the forest soil bacterial community composition and diversity would differ from communities in other forest ecosystems. (33). Similarly, forestry management practices influenced Sequence data from a native Chamaecyparis (NCP) forest the composition of the soil community in low mountain (at and secondary cedar (SCD) plantation soils in YYL eco- around 500 m) forests with less precipitation (2,500 mm) in system (31, 33), and a Cunninghamia konishii Hay (CNH) Lienhuachi Experimental Forest (LHCEF). Here, the most plantation and native hardwood forest (HWD) soils in abundant group of community shifted from Proteobacteria Lienhuachi Experimental Forest (LHCEF) (32) were used for in natural hardwood forest soils to Acidobacteria in comparison in the present study. Because similar methods Cunninghamia konishii Hay plantation soils (32). were used at all of these sites, these comparisons were not Based on our previous studies, bacterial diversity was very biased by methodological differences. These results improve low in the pristine perhumid forest soils at YYL and was our knowledge of bacterial communities inhabiting sub- much less than in comparable soils at LHCEF, which have tropical forest soils in Taiwan and the influences of forest management on bacterial communities in low mountain and * Corresponding author. E-mail: [email protected]; perhumid forest soils. Tel: +886–2–2787–1180; Fax: +886–2–2789–9624. 326 LIN et al.

Materials and Methods Phylogenetic dendrogram construction The CNH, SCD, HWD and NCP bacterial community was Site description and soil sampling described previously (31–33) and is included for comparison. The This study was conducted in Huoshaoliao (HSL), a subtropical sequences were screened against those in the NCBI GenBank low mountain area in northern Taiwan (24°59'52'' N, 121°45'15'' database using the BLAST program. Phylogenetic relationships were E). The elevation is about 300 m a.s.l., the mean annual precipitation analyzed as described (31). Phylogenetic trees were constructed by is more than 4,000 mm, and the mean annual temperature is about the neighbor-joining method (40) with PHYLIP v3.6 (15). Bootstrap 21°C. This region is covered with secondary broad-leaved forest values (14) were created with 100 replicates. and was subjected to extensive timber harvesting for construction during coal mining and for firewood. Large-scale human disturbance Library comparison and diversity estimates ceased after abandonment of the coal mines about 30 years ago. Distance matrices calculated using DNADIST in PHYLIP were Soil samples were collected in June, 2007. Three replicates of used as the input file for the DOTUR program (41). Rarefaction 50 m×50 m plots were selected at the sampling location. Each analyses, richness, evenness, Shannon diversity index (H) and Chao1 replicate was separated by at least 50 m. The soils were collected estimates were calculated for operational taxonomic units (OTUs) with a soil auger 8 cm in diameter and 10 cm deep. Three subsamples with an evolutionary distance (D) of 0.03 (or about 97% 16S rRNA collected from each plot were combined. Visible detritus, such as gene sequence similarity). To analyze the distribution of abundant roots and litter, were manually removed prior to passing through a taxa within libraries, groups were constructed using DOTUR at a 2-mm sieve. Soils were then stored at −20°C for a few days before distance of ≤0.03. These groups were then analyzed by Fisher’s DNA extraction. The soil is clay loam, with a pH value of 4.5, exact test (1). UniFrac (35) analysis was used to compare the clone −1 organic carbon content of 33.4 g kg , and total nitrogen of 2.7 g libraries based on phylogenetic information. The UniFrac Signifi- −1 kg . Details of the properties of the studied soils are listed in Table 1. cance test option with 100 permutations was used to test the significant difference of each pair of samples. The Jackknife 16S rRNA gene clone library construction Environment Clusters were used with the weighted algorithm, which The 16S rRNA clone library was constructed as described considers relative abundance of OTUs, and the normalization step. previously in Lin et al. (31). In brief, soil communities DNA were extracted using an UltraClean Soil DNA Extraction kit (MoBio Nucleotide sequence accession numbers Industries, Carlsbad, CA, USA) in accordance with the manufac- The entire clone sequences obtained in the present study have turer’s instructions. The bacterial SSU rRNA genes were amplified been deposited in the GenBank database under accession numbers by PCR with the primer set 27F and 1492R (27). After 15 cycles, GU936315–GU936424, GU936426–GU936448 and GU936450– the PCR products were cloned using the TOPO TA cloning kit GU936478. (Invitrogen, Carlsbad, CA, USA) and the pCR2.1 vector. White colonies on selective Luria-Bertani (LB) agar plates were placed in Results 96-well plates containing 1 mL LB broth plus kanamycin (50 μg −1 mL ), and grown overnight. Sterile glycerol was added to a final Phylogenetic groups represented in clone library concentration of 10%, and an aliquot was transferred to a 96-well sequencing plate. Both the sequencing and original culture plates About 55 clones of 16S rRNA genes were derived from were stored at −80°C. each replicate sample. The sequences from three replicates were then combined for further analysis. We obtained 164 DNA sequencing and taxonomic assessment clones, and the length of the analyzed sequences was about Bacterial clones were partially sequenced using primer 27F. Sequence analysis was performed using an ABI PRISM Big Dye 630 bp. Two chimeric sequences were detected, and other Terminator cycle sequencing ready reaction kit (Applied Bio- resulting sequences were used for further analysis. Compar- systems, Foster City, CA, USA) and an ABI 3730 Genetic Analyzer isons of the replicate samples showed that they were not (Applied Biosystems) following the manufacturer’s instructions. significantly different (data not shown). Thus, the experimen- Sequences were analyzed with the Mallard and Pintail programs to tal strategy used for sampling, extracting DNA and preparing test for chimeras (2, 3). Taxonomic assignment of sequences was clone libraries appeared to be repeatable. All clones were performed using the naïve Bayesian rRNA classifier (47) in the classified into 11 phylogenetic groups (Table 2). The most Ribosomal Database Project (RDP) (http://rdp.cme.msu.edu/ index.jsp). The distribution of phylogenetic groups among libraries abundant groups were Acidobacteria and Proteobacteria, was then analyzed by Fisher’s exact test (1). comprising more than 70% of all clones. The remaining phyla, Sequences were named as follows: sequence HSL101 composed such as Planctomycetes and Actinobacteria, were all less than of a six-character code that signified the source, the Huoshaoliao 4% of the clones (Table 2). In addition, about 12% of clones (HSL) Forest, the sample replicate in the first number (1 in this were only distantly related to cultured bacteria and were case), and a two-digit unique indicator of the sequence (01 in this designated as the unclassified bacteria group. These clones case). included a representative of the deeply branching but so far

Table 1. Soil chemical and physical properties of study sites Study site pH Organic C (g kg−1) Total N (g kg−1) Sand (%) Silt (%) Clay (%) Soil group Texture HSL 4.5 33.4 12.4 37.5 28.7 33.8 Dystrudept Clay loam CNHa 3.7 44.4 3.2 39.6 33.5 26.9 Dystrudept Clay loam SCDb 3.7 145.0 8.5 3.7 79.9 16.4 Dystrochrept Silt loam HWDa 4.0 38.1 2.7 27.2 38.7 34.1 Dystrudept Clay loam NCPc 3.4 474.0 22.9 3.9 53.1 43.0 Dystrochrept Silty clay a Data from Lin et al. (32). b Data from Lin et al. (33). c Data from Lin et al. (31). Soil Bacterial Community in a Perhumid Forest 327

Table 2. Phylotype of clones in 16S rRNA gene libraries Clones library (% of clones)a Phylogenetic group Total HSL CNHb SCDc HWDb NCPd Acidobacteria 43.8b 57.3a 47.5ab 16.0c 19.0c 38.1 Actinobacteria 3.7b 1.3b 3.5b 12.7a 16.5a 7.0 Bacteroidetes 0.6b 1.9ab 3.5ab 4.7a 0.0b 2.3 Chloroflexi 1.2 1.9 1.2 0.0 0.0 0.9 Firmicutes 0.0b 3.8a 2.7ab 1.3ab 0.0b 1.7 Gemmatimonadetes 1.9 1.9 2.3 0.0 0.6 1.5 Nitrospira 0.6 0.0 0.4 0.0 0.0 0.2 Planctomycetes 3.1ab 1.9ab 3.9ab 1.3ab 7.0a 3.5 Proteobacteria 30.9b 17.2c 29.0b 53.3a 50.6a 35.2 Alphaproteobacteria 17.9a 8.3b 17.4a 10.0ab 16.5a 14.4 Betaproteobacteria 1.9c 0.6c 3.9c 10.7b 25.3a 7.9 Gammaproteobacteria 4.3b 7.6b 3.9b 46.0a 7.6b 9.8 Deltaproteobacteria 6.2a 0.6b 3.5ab 2.0a 1.3b 2.8 Unclassified Proteobacteria 0.6 0.0 0.4 0.0 0.0 0.2 Verrucomicrobia 2.5 3.8 0.4 2.0 2.5 2.0 Unclassified bacteria 11.7a 8.9ab 5.8b 8.7ab 3.8b 7.6 Total (all taxa) 162 157 259 150 158 886 a Data with the same letter in each row indicate no significant difference according to LSD-test at P<0.05. b Cunninghamia konishii Hay (CNH) plantation and natural hardwood forest (HWD) at LHCEF (32). c Secondary cedar (SCD) plantation at YYL (33). d Native Chamaecyparis (NCP) forest at YYL (31). uncultured candidate division WS3. The distribution of bacterial phyla at HSL was very similar to that at SCD, being significantly different for only the unclassified bacterial group. In contrast, in the libraries from the native forest soils at NCP and HWD, the most abundant phylum was Proteobacteria, which accounted for more than half of all clones, and the Acidobacteria were all less than 20% (Table 2) (31, 32). In the Acidobacteria, clones were further clustered into subdivisions 1–3, 5–7 and 17 (Fig. 1) according to the studies of Hugenholtz et al. (19). Most of the clones were in subdivision 1 and 2. For instance, the most abundant clone, HSL104, was in subdivision 1. In the phylum Proteobacteria, Alphaproteobacteria was the most abundant class, followed by Deltaproteobacteria and Gammaproteobacteria (Table 2). Within the Alphaproteobacteria, an abundant OTU with seven sequences was related to Rhodoplanes spp. (Fig. 2). Other bacterial taxa closely related to the soil clones included Bradyrhizobium, Caulobacter and Rhizobium spp. (Fig. 2). About 5% of clones were affiliated with an unclassified alphaproteobacterial group. Diversity and abundant OTUs in soil bacterial community In order to calculate diversity indices, OTUs were formed at D≤0.03 (about 97% sequence similarity). These indices, including the Shannon diversity index, Chao1 nonparametric richness estimators and richness, revealed that the soil Fig. 1. Phylogeny of representative Acidobacteria clones for each bacterial community of HSL was highly diverse (Table 3). OTU. OTUs were formed at evolutionary distances ≤0.03. Clones Rarefaction curves analysis also showed that the diversity of derived in this study are shown in bold. Subdivisions are indicated by this community was higher than in communities in the other brackets. The number of sequences for each OTU is in parentheses fol- four forest soils (Fig. 3). The failure of the rarefaction curves lowing the clone name and GenBank accession number. The names of the sequences consist of a six-character code that signifies the source to plateau indicated that these communities were incompletely from Huoshaoliao (HSL) forest, and other numbers as described in the sampled (Fig. 3). Nevertheless, the slopes of curves for HSL Methods. Numbers at nodes denote bootstrap confidence values soil community were steeper than those for disturbed soils. obtained with 100 resamplings; values ≤70 are not shown. Scale bar Examination of the sizes of abundant OTUs supported the indicates 0.1 substitutions per nucleotide position. 328 LIN et al.

Fig. 3. Rarefaction curve analysis for Huoshaoliao (HSL) forest ( ), Cunninghamia konishii Hay (CNH) plantation ( ), secondary cedar (SCD) plantation ( ), natural hardwood forest (HWD) ( ), and native Chamaecyparis (NCP) forest ( ) soil libraries. OTUs were defined as sequences sharing 97% nucleotide sequence similarity. Values of CNH, SCD, HWD and NCP were calculated from data in Lin et al. (31–33).

Fig. 2. Phylogeny of representative Alphaproteobacteria clones. Notation is as described for Fig. 1. significantly different from the natural forest soil communi- ties (P=0.001) at both YYL and LHCEF. In cluster analyses of the clone libraries, the HSL community was in the cluster above results. In HSL soils, 59% of the clones were single- formed by the disturbed soil communities, and separated from member OTUs or singletons. By comparison, CNH and SCD that formed by the natural communities, HWD and NCP soils soils at LHCEF and YYL, respectively, 48% and 38% of the at LHCEF and YYL, respectively (Fig. 4). clones were singletons. For natural forests, HWD and NCP Differences in composition were also identified by soils at LHCEF and YYL, respectively, less than 20% of examination of the abundant OTUs or those higher than 6 clones were singletons. In addition, from the richness, Chao1 (Table 4). Because representatives of each OTU were estimator and rarefaction curve analysis, the three disturbed obtained from independent replicates in multiple sampling forest soil communities were all more diverse than the two locations and the representation was similar in the different natural communities (Table 3; Fig. 3). sample replicates (data not shown), their abundance was not due to PCR or cloning artifacts or to a single unusual sample. Abundant OTUs in soil bacterial communities Only 16% of clones were in abundant OTUs≥6 (Table 4). Analyses of composition differences of communities also These clones were representative of Acidobacteria and revealed the distinctness of the HSL and other forest soils. Alphaproteobacteria. The most abundant OTU was affiliated UniFrac Significance analyses were used to compare the with subdivision 1 of the Acidobacteria. One abundant bacterial communities on the basis of phylogenetic informa- Alphaproteobacteria-affiliated OTU, represented by clone tion. The P-values revealed that the HSL community was HSL125, was also abundant in NCP soils (Table 4). Other

Table 3. Diversity indices for soil bacterial communities as represented in 16S rRNA gene libraries

Index HSL CNHa SCDb HWDa NCPc Sd 118 104 148 76 56 Ne 162 157 259 150 158 Evennessf 0.96 0.96 0.95 0.88 0.86 Richnessg 0.59 0.48 0.38 0.35 0.15 Shannonh 0.97 0.97 0.98 0.95 0.86 Chao 1 444 262 338 168 76 95% Chao 1 290–734 188–404 257–480 120–267 64–109 Calculations were based on operational taxonomic units formed at an evolutionary distance of <0.03 (or about 97% similarity). a Data from Lin et al. (32). b Data from Lin et al. (33). c Data from Lin et al. (31). d S defined as the number of operational taxonomic units observed. e N defined as the number of sequences. f Evenness defined as H/log S, where the maximum value is 2.3. The observed/maximum possible value is reported. g Richness=(number of singleton OTUs-1)/logN. The maximum value is (N-1)/logN. The observed/maximum possible value is reported. h Shannon diversity index (H). The observed/maximum possible value is reported. Soil Bacterial Community in a Perhumid Forest 329

Table 4. Distribution of the most abundant OTUs in 16S rRNA gene clone librariesa Clone library Clone nameb Taxonomic affiliationc Nd HSL CNHe SCDf HWDe NCPg NCP106 Burkholderia (AJ292637) 0b 0b 3b 2b 25a 30 HWD201 Stenotrophomnas (FJ894817) 0b 0b 0b 28a 0b 28 CNH314 Acidobacteria sp. (AY963487) 2b 11a 0b 4ab 0b 17 HSL125 Rhodoplanes sp. (AY917444) 7a 1ab 1ab 0b 5ab 14 HSL104 Acidobacteria sp. (EU445213) 9a 3ab 0b 0b 0b 12 HSL133 Acidobacteria sp. (EF075731) 6a 2ab 3ab 0b 0b 11 NCP138 Bradyrhizobium sp. (AY326607) 2 0 3 0 4 9 HWD214 Serratia sp. (GU120657) 0b 1b 0b 7a 0b 8 NCP108 Burkholderia sp. (AM268320) 0b 0b 0b 0b 7a 7 a OTUs formed at an evolutionary distance of ≤0.03 (or about >97% similarity). Data with the same letter in each row indicate no significant difference according to LSD-test at P<0.05. b Representative clone for each OTU. c The GenBank accession number of the closest relative is listed in parentheses. d Total number of clones in an OTU. e Data from Lin et al. (32). f Data from Lin et al. (33). g Data from Lin et al. (31).

compaction and those with harvesting plus complete surface organic matter removal with heavy soil compaction (4). Harvesting in this disturbed forest caused loss of the shading overstory, and exposure to sunlight might lead to soil temperature fluctuation and water loss. Increased availability + of NH4 has been reported for clear-cut treatments (43). Differences in nitrogen input could affect organic matter decomposition and thus result in microbial community and/ or decomposing-enzyme shifts (24). The soil C-to-N ratio and the response of trees to this ratio all influence soil microbial community composition (18). Forestry manage- Fig. 4. A dendrogram from UniFrac Jackknife Environment Clusters ment could also influence several environmental factors analysis of 16S rRNA gene clone libraries. Analysis involved weighted data. Numbers at nodes indicate the frequency with which nodes were simultaneously. Thus, discriminating the effects of an supported by Jackknife analysis. The length of the scale bar indicates a individual factor on the community is difficult. distance of 0.02. Compared with the bacterial community of evergreen broad-leaved subtropical forests in south-west China (10) and abundant OTUs derived from HSL were less abundant or tropical forests in Brazil and Malaysia (6, 20), the HSL absent from other perhumid and low mountain forest soils community was highly diverse. In this study, it was also more (Table 4). diverse than in natural and disturbed forest soils at LHCEF and YYL. Our previous study of LHCEF and YYL reported Discussion that disturbance by forestry management increased the diversity of soil bacterial communities (32, 33), and the Our results reveal that the bacterial community composi- severity of disturbance affected the degree of community tion in disturbed HSL forest soils differed greatly from natural diversity (33). The highly diverse community in HSL supports forest ecosystems. In all 16S rRNA gene clone libraries, this conclusion, and suggests that the disturbance of HSL Acidobacteria and Proteobacteria were the major phyla, but soils was more severe than that of other disturbed forest soils. their relative abundances between natural and disturbed forest Furthermore, even the disturbed forest soils in YYL were soils were different. For instance, in HSL soils, the proportion lower than in HSL, indicating high diversity in warmer of Acidobacteria was 44%, while in HWD soils they climate conditions. The altitude of YYL forest is higher than comprised only 16% of all clones. Within the Proteobacteria, HSL forest. Increased altitude is accompanied by increased Gammaproteobacteria and Betaproteobacteria were the environmental harshness, especially a lower annual temper- most abundant groups in natural forest soils at HWD and ature, and decreased bacterial diversity (34, 42). In addition, NCP, respectively; in contrast, Alphaproteobacteria was high precipitation in HSL forest could maintain high soil the most dominant group in HSL soils. Differences in water content and, in turn, influence diversity by controlling soil bacterial communities have been detected when com- nutrient availability and cell movement (49). paring undisturbed forests and pastures established from Molecular surveys have found Acidobacteria in a cleared forest land (22, 37). Proportional differences in wide variety of environments (5, 23, 50). In this study, gammaproteobacterial-affiliated clones were also found Acidobacteria were also the dominant phyla in the com- between forests with whole-tree harvesting without soil munity; however, these clones are not closely related to 330 LIN et al. known species of this phylum, Acidobacterium capsulatum soil bacterial communities in disturbed forest ecosystems is (25), Geothrix fermentans (11) and Holophaga foetida needed to address the impact of forest managements on (30). Hence, predicting function from their properties is ecosystem function. not possible. The Acidobacteria might also be metabol- ically active as well as numerically dominant in soils (29). References It is important to examine the functional diversity of Acidobacteria further to elucidate their ecological roles. 1. Agresti, A. 1992. A survey of exact inference for contingency tables. Stat. Sci. 7:131–153. One Alphaproteobacteria OTU, represented by clone 2. Ashelford, K.E., N.A. Chuzhanova, J.C. Fry, A.J. 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