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Article

Research article

J. Microbiol. Biotechnol. 2019; 29(3): 441-453

Published online March 28, 2019 https://doi.org/10.4014/jmb.1809.09007

Copyright © The Korean Society for Microbiology and Biotechnology.

Responses of Soil Bacterial and Fungal Communities to Organic and Conventional Farming Systems in East China

Hanlin Zhang 1, 2, 3, Xianqing Zheng 1, 2, Naling Bai 1, 2, Shuangxi Li 1, 2, Juanqin Zhang 1, 2 and Weiguang Lv 1, 2*

1Eco-environmental Protection Institute, Shanghai Academy of Agricultural Science, Shanghai 201403, P.R. China
2Agricultural Environment and Farmland Conservation Experiment Station of the Ministry of Agriculture, Shanghai 201403, P.R. China
3Shanghai Key Laboratory of Horticultural Technology, Shanghai 201403, P.R. China

Correspondence to:Weiguang  Lv
lwei1217@sina.com

Received: September 6, 2018; Accepted: January 31, 2019

Abstract

Organic farming is considered an effective form of sustainable agricultural management. However, understanding of soil microbial diversity and composition under long-term organic and conventional farming is still limited and controversial. In this study, the Illumina MiSeq platform was applied to investigate the responses of soil bacterial and fungal diversity and compositions to organic farming (OF) and improved conventional farming (CF, applied straw retention) in the rice-wheat rotation system. The results highlighted that the alpha diversity of microbial communities did not differ significantly, except for higher bacterial diversity under OF. However, there were significant differences in the compositions of the soil bacterial and fungal communities between organic and conventional farming. Under our experimental conditions, through the ecological functional analysis of significant different or unique bacterial and fungal taxonomic members at the phyla and genus level, OF enhanced nitrogen, sulfur, phosphorus and carbon dynamic cycling in soil with the presence of Nodosilinea, Nitrospira, LCP-6, HB118, Lyngbya, GOUTA19, Mesorhizobium, Sandaracinobacter, Syntrophobacter and Sphingosinicella, and has the potential to strengthen soil metabolic ability with Novosphingobium. On the other hand, CF increased the intensity of nitrogen cycling with Ardenscatena, KD1-23, Iamia, Nitrosovibrio and Devosia, but enriched several pathogen fungal members, including Coniochaeta, Corallomycetella, Cyclaneusma, Cystostereum, Fistulina, Curvularia and Dissoconium.

Keywords: Bacterial and fungal community, high throughout sequencing, rice-wheat rotation, organic and conventional farming

Introduction

As highly abundant species, bacterial communities are multifunctional and indispensible in soil ecological processes, and apt to degrade the labile organic matter [1, 2]. Fungi communities are important decomposers in the soil ecosystem, who can decompose plant residues and recalcitrant compounds, releasing nutrients during the degradation process for plant growth [3]. The diversities in soil bacteria and fungi communities have been often considered as bioindicators revealing soil quality conditions of anthropogenic ecosystems. In general, greater bacterial and fungal diversity indicates more stable and healthier soil ecosystems [4].

In recent years, excessive input of chemical fertilizers, pesticides and herbicides has led to serious agricultural soil ecological problems, such as soil hardening, acidification and degeneration [5]. In this case, organic farming has been brought to attention. Organic farming prohibits the use of chemical products such as fertilizers and pesticides; promotes material circulation in the internal system and increases the input of organic matter [6]. The main organic farming measures include the application of organic fertilizer, straw retention, green manure rotation and physical and biological means to prevent crop diseases and pests [7, 8].

Some studies have reported that after long-term organic farming, microbial diversity and evenness was significantly higher than that of conventional farming. Several researchers found that organic farming can shift and enhance beneficial microbial taxa such as Burkholderia, Mesorhizobium, Rhizobium for crops [5, 9]. However, the comparative analysis results between organic farming and conventional farming are not consistent. Some analyses showed manures used in organic farming may introduce fecal microbial contamination containing some pathogenic flora into soil. Other studies reported that compared to conventional farming, there were no significant differences or even lower microbial diversity in organic farming [8]. Therefore, it is of great significance to explore how soil microbial diversity differs across regions and farming types.

Chongming Island is located in Shanghai, East China. Currently, organic farming is vigorously advocated in the intensive farming of Chongming Island. At the same time, conventional farming in Chongming Island has also been improved with assembly technology, such as crop straw retention. However, the effects of long-term organic and improved conventional farming management on soil bacterial and fungal community structures were not clear.

In this study, based on long-term field experiment, the Illumina MiSeq approach was employed to investigate soil bacterial and fungal community diversity over 12 years of continuous organic and conventional rice-wheat rotation farming systems in Chongming Island, which accounted for the most widely planted cropping pattern in East China. The aims of this research were 1) to determine and compare the bacterial and fungal community structures under organic and conventional farming; 2) to identify the shifted bacterial and fungal taxa, and associate their functions with a specific farming system; 3) to detect the relationship between soil physico-chemical properties and the bacterial and fungal community structures, and finally provide a theoretical basis for conducting the most ecological and sustainable farming system that best promotes the soil microbial community.

Materials and Methods

Site Description and Experimental Design

The long-term organic and conventional comparison experiment took place at Yangzi Farm on Chongming Island, Shanghai, China (121°55’ E, 31°66’ N). The annual average temperature and precipitation of this area are 15.3 degrees and 1,003.7 mm, respectively; there are 229 d of frost-free period in a year. The terrain is flat, and the range of elevation is from 3.5 m to 4.5 m. The soil type is sandy loam.

The experiment started from the wheat season of 2004, and ended in the rice season of 2015. There were 2 treatments, organic farming (OF) and conventional farming (CF), and each treatment had 8 replicates. Every replicate field was 40 m × 20 m in length and width (800 m2), and all the replicates were arranged in random block design. The detailed management for both of the 2 treatments are shown in Table 1. The amount of fertilizer input in the 2 treatments is set according to the average application used in the rice-wheat rotation systems in Chongming Island. In both OF and CF, the same amount of pure nitrogen (555 kg•ha ) was applied annually from 2014-2015. Prior to 2004, the same conventional farming management had been applied to all these experimental plots.

Table 1 . Detailed management of the long-term organic and conventional farming experiment..

System/TreatmentOrganic Farming (OF)Conventional Farming (CF)
Fertilizer typesCommercial organic fertilizeraSynthetic fertilizerb
YearlyTotal nitrogen (TN)555555
Fertilizer Input (kg•ha-1)Total phosphorus (TP) 206213
Total potassium (TK)13593
Plant protection schemeWeed controlMechanicalMechanical and herbicidesc
Disease controlBiological pesticidesChemical pesticidesc
Pest controlBiological pesticidesc and biological control measuresdChemical pesticidesc
Special treatmentsStraw retentione (total amount) Straw retentione (total amount)

a: the commercial organic fertilizer used in OF was measured every year before applied, and pure nitrogen content kept the same amount from 2004 to 2015. The commercial organic fertilizer was derived from livestock manure, and the average nutrients contents were as follows: organic matter content 489 g•kg-1, TN 25.3 g•kg-1, TP 13.4 g•kg-1, TK 12.7 g•kg-1. .

b: the synthetic fertilizers used in CF were urea and bulk blending fertilizer, and N: P2O5: K2O of bulk blending fertilizer was 15: 15: 15..

c: the biological pesticides, herbicides and chemical pesticides used were all in the list of “Recommended categories of pesticides in Shanghai” from 2004-2015. The application of the pesticides and herbicides were in accord with the plant protection opinions of Agro-Technology Extension Center of Chongming..

d: the biological control measures used contained Trichogramma releasing and Vetiver grass planting technology..

e: straw retention was performed by harvester at the same time with harvesting. Straw was cut into about 10 cm-long pieces, and ploughed to 20 cm depth by rotary tiller..



Soil Sampling and Analysis

Soil samples of the 0-20 cm layer were collected after rice harvest on Nov. 1, 2015 by a soil sampler (the diameter was 5 cm). At each block, 10 random points of soil samples were collected and mixed into one. The soil samples were stored in polyethylene bags and taken back to lab immediately. The above ground roots, visible residue, and stones in soil samples were removed with a 2- mm sieve. One portion of soil samples was freeze-dried for soil properties determination, and the others were stored at -20°C for DNA extraction and microbial analysis.

Soil bulk density was measured using cutting ring method; soil total and available nitrogen were determined by Kjeldahl method; soil total phosphorus was digested by HF-HClO4 and determined by molybdenum-blue colorimetry method, and available phosphorus was extracted by sodium bicarbonate and determined by molybdenum blue method; soil total potassium was determined by digestion with HF-HClO4 and determined by flame photometry method, and available potassium was extracted by ammonium acetate and measured by flame photometry; soil pH was determined by potentiometry (soil -water ratio was 2.5:1); soil organic carbon was determined by dichromate oxidation [10]; soil salinity was measured by gravimetric method; Cu, Zn, Mg, Ni, Ca, Fe, Cd, Cr, and Pb were determined using atomic absorption spectrophotometer [11] (AA6880, SHIMADZU Japan); Hg, As were measured using atomic fluorescence spectrometer (AFS- 2000, China).

DNA Extraction and Sequencing

Soil DNA was extracted using a MoBio PowerSoil DNA Isolation Kit (12888) according to the manufacturer’s instruction. The extracted DNA concentration and quality were determined by spectrophotometer (RS232G, Eppendorf, Germany). Bacterium- biased primers 515F (5’-GTGCCAGCMGCCGCGG-3’) and 907R (5’-CCGTCAATTCMTTTRAGTTT-3’) were used to amplify about 300 bp fragments in V4 and V5 hypervariable regions of the bacterial 16S rRNA gene [12]. Fungi-specific primers ITS5 (5’- GGAAGTAAAAGTCGTAACAAGG-3’) and ITS4 (5’-TCCTCCGCTTATTGATATGC-3’) were used to amplify about 600 bp fragments in ITS1 regions of the fungal gene [13].

The PCR amplifications were carried out in a total volume of 25 µl, containing 40 ng of DNA template, 1.0 µl each primer (10 µm), 0.25 µl Q5 high-fidelity DNA polymerase, 5.0 µl 5* High GC Buffer, 5.0 µl 5*Reaction Buffer, 0.5 µl dNTP (10 mM). Amplifications were conducted with the following thermal conditions: for 16S V4-V5 rRNA genes, 30 sec initial denaturation at 98°C, followed by 25 cycles of denaturation at 98°C for 15 sec, annealing at 50°C for 30 sec, extension at 72°C for 30 sec, and a final extension at 72°C for 7 min; for ITS1 genes, 30 sec of initial denaturation at 98°C, followed by 35 cycles of denaturation at 98°C for 15 sec, annealing at 50°C for 30 sec, extension at 72°C for 30 sec, and a final extension at 72°C for 7 min. After successful amplifications, the PCR products were pooled in equimolar concentrations of 10 ng•µl-1 for sequencing. Sequencing was performed on an Illumina MiSeq sequencer at Personal Biotechnology Co., Ltd. (China).

Raw sequences were put through quality control and assigned on unique 10-bp barcodes. Then the remaining sequences were clustered into operational taxonomic units (OTUs) based on the level of 97% sequence similarity. Quantitative Insights into Microbial Ecology (QIIME, version 1.7.0) was employed to annotate the sequences through BLAST with RDP and Unite databases, which were for bacteria and fungi, respectively.

Statistical Analysis

One-way analyses of variance (ANOVA) with Tukey’s HSD tests were performed to discriminate significant differences among OF and CF using SPSS 19.0. The bacterial and fungal richness and diversity indices (Chao1, Abundance-based and Coverage Estimator (ACE), Shannon and Simpson) were estimated using Mothur (version v.1.30.1) [14]. Redundancy analysis (RDA) was employed to examine the relationship between the microbial community composition and soil agrochemical properties using the vegan package of R software (Version 3.0.2) [15]. PLS-DA (Partial Least Squares Discriminant Analysis) was carried out to investigate the microbial community differences between OF and CF based on OTU results using R software. The top 20 significant differences of group abundance at genus level were revealed through Metastats (http://metastats.cbcb.umd.edu/). The taxonomic and phylogenetic visualization of bacterial and fungal communities was performed though GraPhlAn (http://segatalab.cibio.unitn.it/tools/graphlan) for rapid discovery of dominant microbial groups. Venn diagrams were generated to show the shared and unique genera among OF and CF with the Venn Diagram package of R software.

Results

Soil Agrochemical Properties

Soil nutrients and some mineral element content were measured to investigate the influences of different farming on soil agrochemical properties (Table 2). Soil organic carbon (SOC) under OF was significantly higher than that of CF by 10.7%, probably because of the input of organic fertilizer. OF also changed soil salinity, and it was 50% higher than that for CF. There were no significant differences in pH, bulk density, total nitrogen (TN), total phosphorus (TP), total potassium (TK) and available potassium (AK) between OF and CF. However, the available nitrogen (AN) and phosphorus (AP) were significantly higher under CF compared to OF, by 13.4% and 44.2% respectively. Eleven types of mineral element content were tested and there were no significant differences between OF and CF except for Zn and As. OF showed higher Zn and As content than CF by 10.8% and 25.7%, respectively.

Table 2 . Agrochemical properties of soil samples..

Organic Farming (OF)Conventional Farming (CF)
pH8.41±0.08a8.24±0.11a
Bulk Density (g•cm-3)1.31±0.05a1.33±0.07a
SOC(g•kg-1)15.66±1.08a14.15±0.86b
TN (g•kg-1)1.81±0.10a1.74±0.11a
TP (g•kg-1)1.72±0.12a1.83±0.09a
TK (g•kg-1)12.59±0.71a13.13±0.85a
Available N (mg•kg-1)42.26±3.28b47.94±4.16a
Available P (mg•kg-1)2.49±0.15b3.59±0.21a
Available K (mg•kg-1)127.41±5.25a130.75±6.79a
Soil Salinity (%)0.12±0.01a0.08±0.01b
Cu (mg•kg-1)29.84±2.37a29.93±3.09a
Zn (mg•kg-1)129.42±11.62a116.77±12.13b
Pb (mg•kg-1)20.63±2.10a20.45±3.59a
Cd (mg•kg-1)0.16±0.02a0.14±0.02a
Cr (mg•kg-1)98.60±6.39a98.18±8.04a
Ni (mg•kg-1)35.47±2.36a34.95±3.57a
Fe (g•kg-1)17.81±2.21a19.62±1.79a
Ca (g•kg-1)18.81±2.27a19.32±2.11a
Mg (g•kg-1)8.19±0.80a8.70±0.93a
Hg (mg•kg-1)0.07±0.01b0.13±0.02a
As (mg•kg-1)14.15±2.57a11.26±1.60b

Data in the table are Mean±SE of 8 replicates; Different letters in the same row indicates a significant difference (p< 0.05)..



Bacterial and Fungal Alpha Diversity

Bacterial and fungal community richness and diversity under two farming systems were estimated (Table 3). Chao1 and abundance-based coverage estimation (ACE) were employed as richness indices. Simpson and Shannon indices, which were calculated by richness and species abundance, were used as diversity indices within each individual sample. There were no significant differences of Chao 1 and ACE between OF and CF in bacterial community, whereas OF had significantly higher Simpson and Shannon than CF, which meant OF could increase the diversity of bacterial community. In fungal community, there were no significant differences between OF and CF observed, showing that little change had been made by OF.

Table 3 . Estimated OTU richness and diversity indices of the organic and conventional farming fields..

SimpsonChao1ACEShannon
BacteriaOF0.9947±0.0017a1869±157a2382±182a9.19±0.37a
CF0.9917±0.0054b1623±122a2028±191a8.88±0.51b
FungiOF0.9141±0.0287a361±28a371±21a5.09±0.46a
CF0.9354±0.0293a395±33a407±29a5.32±0.37a

Data in the table are Mean±SE of 8 replicates; Different letters in the same row indicates a significant difference (p< 0.05)..



Bacterial and Fungal Community Composition

Shared and unique genera between 2 farming systems were determined via Venn diagram (Fig. 1). For bacterial community, a total of 2,527 OTUs were detected in both soils, and the numbers of unique genera under OF and CF were 980 (27.9%) and 810 (24.3%), respectively. For fungal community, there were 671 common OTUs in OF and CF, while 187 (22.0%) and 207 (23.6%) OTUs were unique in the soil of organic and conventional farming. Compared to CF, OF increased bacterial OTUs and decreased fungal OTUs, exerting more influences on bacterial community than fungal community.

Figure 1. Venn diagram showing shared and unique genera of soil bacterial and fungal communities in organic farming (OF) and conventional farming (CF). The OTUs were defined at 97% sequence similarity level.

The main bacterial and fungal taxa found in the soil microbiome are shown in Figs. 2 and 3. The dominant bacterial taxon (exceeding 1% of all taxa) across all samples were Proteobacteria (with class of Alphaproteobacteria, Gammaproteobacteria, Deltaproteobacteria and Betaproteobacteria, order of Xanthomonadales, and family of Enterobacteriaceae), Chloroflexi (with class of anaerolineae), Acidobacteria (with class of Acidobacteria-6), Planctomycetes, Bacteroidetes, Crenarchaeota (with class of Thaumarchaeota, order of Nitrososphaerales, and family of Nitrososphaeraceae) and Nitrospirae (with class of Thaumarchaeota, and order of Nitrososphaerales). The relative abundances of above phylum under OF-CF were 39.6%-35.2%, 17.7%-21.8%, 14.9%-14.6%, 4.4%-3.5%, 4.6%-3.8%, 3.4%-4.1% and 3.6%-2.8%, respectively. The dominant fungal taxon (exceeding 1% of all taxa) across all samples were Ascomycota (with class of Sordariomycetes and Dothideomycetes, order of Sordariales and Hypocreales, family of Lasiosphaeriaceae and Nectriaceae, and genus of Podospora, Schizotherium and Zopfiella), Basidiomycota (with class of Agaricomycetes) and Zygomycota (with class of Mortierellales, order of Mortierellaceae, and family of Mortierella). The relative abundances of above phylum under OF-CF were 85.7%-86.7%, 7.3%- 5.3% and 2.8%-4.6%, respectively.

Figure 2. Phylogenetic classification of relative abundance of dominant bacterial (A) and fungal (B) phyla in organic farming (OF) and conventional farming (CF).

Comparison of Microbial Community Composition

Based on species abundances of different treatments, the PLS-DA analysis was performed by calculating the VIP (variable importance in projection) coefficient of each treatment replicate. The greater the VIP value, the greater the replicate’s contribution to group differences. In both Figs. 4A andhe values of the 8 replicates under CF were all negative in X axis, while the values under OF were all positive, which meant there are significant differences in the bacterial and fungal community composition between organic and conventional farming.

Figure 4. Partial Least Squares Discriminant Analysis (PLS-DA) of soil bacterial (A) and fungal (B) communities in organic farming (OF) and conventional farming (CF).

The top 20 significant differences of bacterial and fungal abundance at genus level were separately listed in Figs. 5A and 5B. In the bacterial community under OF, there were 13 genera significantly more abundant than in CF, including 4 unique genera (Arthronema, Lyngbya, Sandaracinobacter and Nodosilinea); while CF had 7 genera significantly more abundant than OF, including 2 unique genera (Ardenscatena and B-42), which indicated that OF had more influence in promoting soil bacterial communities. In the fungal community, CF had 13 genera significantly more abundant than OF, and all of them were unique genera; while OF had 7 genera significantly more abundant than CF, and there was only 1 common genera (Clavulina) with CF. The results showed that the fungal community may be more sensitive to farming systems than the bacterial community, and CF may have more potential to shift the fungal community structure than OF.

Figure 5. The group abundance differences at genus level of soil bacterial (A) and fungal (B) communities in organic farming (OF) and conventional farming (CF) based on Metastats. The top 20 significant differences of group abundance at genus level were listed as separate figures.

Effects of Soil Agrochemical Properties on Bacterial and Fungal Communities

The relationships between soil environmental variables and microbial compositions were investigated by using Redundancy analysis (RDA). The length of the corresponding arrows indicates the relevance of the environmental variables for explaining the variation in microbial community. For bacteria (Fig. 6A), the eigenvalues of the first and second axes in the two-dimensional diagrams are RDA1: 36% and RDA2: 21%. The model explained 57% of the whole bacterial variance. Sixteen replicates under different farming systems were significantly clustered. The soil bacterial community showed a strong response to soil agrochemical properties. The bacterial community exhibited a significantly positive relationship with pH under OF, and showed a positive relationship with TP and available N under CF. For fungi (Fig. 6B), the eigenvalues of the first and second axes in the two-dimensional diagrams are RDA1: 22% and RDA2: 13%. The model explained 34% of the whole fungal variance. The fungal response to soil agrochemical properties was weaker than that of the bacterial community. The fungal community still exhibited a significantly positive relationship with pH under OF, and showed a positive relationship with Pb and Cu under CF.

Figure 6. Redundancy analysis (RDA) of abundance of soil bacterial and fungal (B) associated with environmental variables. The numbers indicate 16 replicates of organic farming (OF) and conventional farming (CF). Environmental variables are indicated by arrows.

Discussion

Organic farming is widely recognized as an effective way of sustainable agricultural management. Commonly, organic farming is considered to improve soil and crop quality [8]. However, because of the lower crop yields compared to conventional farming, governments and farmers hesitated at large-scale promotion [16]. For the purpose of building a world-class ecological island, organic farming was applied from 20 years ago in Chongming Island. At the same time, conventional farming was also improved by the mandatory application of straw retention in grain fields. Although the comparative study of soil microbial communities in organic and conventional farming has been carried out a lot, various climate and geography related factors made the effects of different farming systems complex and controversial [5]. Therefore, the present study of bacterial and fungal communities of organic and improved conventional farming in Chongming Island could provide better understanding and the potential to optimize the agricultural farming management.

Soil agrochemical properties are influenced by different farming systems. In the present research, compared to CF, OF raised SOC, Zn and As significantly, and decreased available N, available P and Hg (Table 2). These results were consistent with some previous research: the high input of organic matters under OF caused the increase of SOC [17], and Zn and As went into soil with the organic fertilizer derived from livestock manure [18], whereas chemical phosphate fertilizer contained a higher amount of Hg than organic fertilizer, which could be an explanation for the higher Hg concentration under CF. However, among 21 soil nutrient and mineral measurement indexes, there were 15 indexes with no significant differences between OF and CF, which probably was led by the almost equal total fertilizer input and straw retention.

In this long-term experiment, the bacteria and fungi communities also responded to changes in soil agro- chemical properties. The increment of bacterial and fungal community under OF showed similar response and were directly related to the change of soil pH (Fig. 6), which confirmed previous thinking that pH has a strong influence on soil microbial diversity and community structure [19]. Under CF, soil nutrient (TP and available N) had direct effects on bacterial community structure, and soil mineral content (Pb and Cu) was related with fungal community, suggesting that synthetic fertilizer input had likely a stronger effect on bacteria, while the source of mineral content under CF straw retention altered the fungal community more.

Based on the alpha diversity analysis (Table 3), our findings evidenced that OF hosts a more even bacterial community than CF, whereas no significant differences were observed on the richness and evenness of the fungal community between OF and CF. In this present study, both treatments used a tillage method with an almost identical degree of perturbation, causing the same soil bulk density (Table 2), which should be major contributors to the same abundances of fungal community [3]. A Venn diagram (Fig. 1) showed that different farming systems exerted more effects on bacteria than fungi. The ratios of special and common OTUs were 70.8% (bacteria) and 43.8% (fungi), respectively. There were some recent studies showing that compared to richness, soil microbial community evenness plays a more important role in maintaining soil ecosystem health [20], which meant OF had the potential to improve or revitalize the ecological function of the soil bacterial community. A number of comparative tests have also confirmed that organic farming enhanced soil bacterial abundance and diversity under different geographic and soil conditions [21].

PLS-DA demonstrated that the soil bacterial and fungal communities of two farming systems could be separated completely at the 97% OTU level (Fig. 4), showing significant differences in bacterial and fungal community structure. OF samples tended to cluster with each other at higher similarity than the samples under CF in both bacterial and fungal communities, and the microbial community structure under OF was more stable than that under CF. There have been several other studies revealing similar tendency. Compared to conventional farming along the lower reaches of the Yangtze River in China, organic farming with 3 different crops shared a similar microbial community structure, but the PCA results showed a more centralized bacterial cluster under organic farming [22]. NMDS analyses demonstrated significant soil microbial community differences according to the samples from 93 conventional, organic and wild olive orchards in southern Spain [23].

According to the bacterial phylogenetic classification of relative abundance (Fig. 3A) and a phylogenetic tree diagram (Fig. 2A), all of the bacterial communities were dominated by twelve major groups at phyla level (the relative abundance > 1%), especially by Proteobacteria, Chloroflexi and Acidobacteria, which were broadly dispersed across the phylogenetic groups found in soil [5]. Proteobacteria was considered to have the ability to degrade recalcitrant organic compounds and beneficial for crop productivity, and mostly found abundant in conventional farming soil [24]. However, recently Proteobacteria was also detected in some organic farming soil [25], and even with higher relative abundances than conventional farming. The present study showed that Proteobacteria had the most abundance and was statistically equal under OF and CF. Among these twelve major groups, there were only two phyla with significant differences between OF and CF. Nitrospirae had more abundance under OF than CF, and Actinobacteria was to the contrary. Nitrospirae had the ability of nitrite-oxidizing, and could convert NO2- to NO3- [26]. The increasing of Nitrospirae was observed in the change from desert to oasis [27] and from non-cultivated soil to cultivated soil [28]. With higher proportion of Nitrospirae represented, soil nitrogen cycling under OF may be more active than under CF. Actinobacteria was known for its cellulose degradation capability and its abundances were normally positive associated with crop straw decomposing ability [29]. In our study, the total amount of straw retention was applied both under OF and CF. However, there were differences between the total amount of straw under OF and CF because of the different crop yields (The crop yield under OF normally was 15%-20% lower than CF). That probably was the reason why Actinobacteria had lower proportion under OF.

Figure 3. The phylogenetic tree diagram of soil bacterial (A) and fungal (B) communities in organic farming (OF) and conventional farming (CF) based on GraPhlAn. The phylogenetic tree shows the overall sample, from the phylum to the genus (from the inner to the outer ring arranged in sequence). The size of the point represents the average relative abundance of the taxon, and the relative abundance of the first 20 taxa is also identified with letters.

All of the fungal communities (Figs. 2B and 3B) were dominated by four major groups at phyla level (the relative abundance > 1%), including Ascomycota, Basidiomycota, Zygomycota and unidentified. Ascomycota was considered as an important fungus to degrade lignocellulose organic matter, and has been observed widely in different types of agricultural soil [30]. Ma [31] believed that Ascomycota was the dominant fungal member in the process of crop straw decomposition. Our results were also consistent with this observation. The relative abundance of Ascomycota was the highest, averaging 86.2%. Among these four major groups, Zygomycota was the only phyla with significant differences between OF and CF. Zygomycota was able to degrade plant debris and other more resistant organic matter [32], and formed symbiotic relationships with plant roots [33]. Our results showed that the relative abundances of Zygomycota under CF were more significant than in OF, probably because the amount of crop yield (plant roots) under CF was much more than in OF.

In the present study, based on the bacterial and fungal information at phyla level, only a few taxonomic groups respond differently to farming system. However, on one hand, generally there will be two or even more ecological characteristics in one taxonomic group [21]; on the other hand, according to the recent research, the lower taxonomic members could reveal more complex ecological functions than the major groups [34]. Therefore, more analyses at lower taxonomic levels were needed to describe the detailed differences of the microbial communities.

The top 20 significant taxonomic differences at genus level were investigated using Metastats (Fig. 5). Among these 20 bacterial taxonomic members, there were 13 species whose abundances under OF were more than those of CF, namely Novosphingobium, Sandaracinobacter, Syntrophobacter, Inquilinus, Sphingosinicella, GOUTA19, Mesorhizobium from Proteobacteria, Arthronema, Lyngbya, Nodosilinea from Cyanobacteria and LCP-6, HB118, Nitrospira from Nitrospirae. Novosphingobium is identified as a metabolically versatile member, which could be found in different soil environments [35]; LCP-6 and HB118 are considered as important contributors to soil phosphorus metabolism [58], and Lyngbya owns the ability to sequester the excess phosphorus and release it slowly [37]; GOUTA19 and Mesorhizobium are both related to sulfur cycling. GOUTA19 was a sulfur-reduction bacterium and found in paddy soil [38]. Mesorhizobium is isolated from root nodules, and involved in sulfur oxidization [39]; Sandaracinobacter, Syntrophobacter and Sphingosinicella are capable of utilizing and degrading organic substrates [40]. Syntrophobacter could decompose fatty acids in paddy soils [41], and polyaromatic hydrocarbons could be degraded to anthranilic acid with the participation of Sphingosinicell [42]; Arthronema could produce phycobiliprotein, which has massive clinical and commercial value [43]; Nodosilinea and Nitrospira are involved in soil nitrogen cycling. Under anaerobic condition, Nodosilinea is good at fixing N2 in soil [44], and the higher Nitrospira abundance indicates that nitrite oxidation activity in soil is relatively low [45]; one part of Inquilinus members are human pathogens [46], which probably comes from organic fertilizer derived from livestock manure. On the contrary, there were 7 species whose abundances under OF were less than those of CF. Ardenscatena, KD1-23, Iamia, Nitrosovibrio and Devosia are all involved in nitrogen cycling. The first three species could enhance the strength of soil denitrification [20, 47], and the ecological functions of the last two species are about ammonia oxidization and N fixation, respectively [48, 49]; B-42 is a member of the Methylothermaceae, which contains the enzymes for aerobic methane oxidation and reduces methane emission [50]; Azoarcus has the ability to degrade aromatic compounds under anaerobic conditions [51]. In summary, compared to CF, the bacterial community under OF may have the potential to weaken soil nitrogen cycling intensity to reduce the nitrite leaching and N2O emission, but enhance soil sulfur, phosphorus and carbon metabolism, increasing CH4 emission.

Among these 20 fungal taxonomic members, there were 7 species whose abundances under OF were more than those in CF, namely Blastobotrys and Gliocladiopsis from Ascomycetes, Campanophyllum, Clavulina and Cystofilobasidium from Basidiomycetes, Catenaria from Blastocladiomycetes and Diversispora from Glomeromycetes. Blastobotrys could decrease the Fusarium sesquiterpenoid toxins by converting it to less toxic products [52]; Gliocladiopsis was often isolated from diseased plants, but no evidences showed it was a pathogen [53]; there were no studies about Campanophyllum and Diversispora describing its ecological functions; Clavulina holds a relatively stronger ability for Ca retention than the other fungi in underground soil [54]; Cystofilobasidium are observed widely in cold areas, and may degrade pectin by its produced enzymes [55]; Catenaria was found parasitizing nematodes in nature, and brings a potential way to control nematodes in the future [56]. CF had 13 fungal taxonomic members (9 species from Ascomycetes, 3 species from Basidiomycetes and 1 species from Glomeromycetes), which were more enriched than OF. Cladorrhinum was reported to promote plant growth only when the soil fertility was relatively low [57]; Dentiscutata was found to intensely reduce the capacity of soil ecosystem metabolism [58]; Coniochaeta, Corallomycetella, Cyclaneusma, Cystostereum, Fistulina, Curvularia and Dissoconium are all different kinds of fungal pathogens. The first five fungal species can infect plant roots causing woody disease and decay [59-61]; the members of Curvularia contain several types of plant pathogens, and also include some pathogens causing opportunistic human infections [62]; Dissoconium could cause complex plant disease on the surface of several types of fruits [63]. The ecological functions of Arachnopeziza, Chlorophyllum, Coniolariella and Fusicolla are still not clear. To sum up, the fungal community under OF could alleviate the negative effects of some toxins and nematodes, and benefit soil nutrient cycling and mineral element accumulation. On the contrary, under the effects of CF, several plant and human pathogens were enriched in the fungal community, and the metabolic capacity of the soil ecosystem was weakened.

In conclusion, compared to conventional farming, organic farming significantly improved SOC and bacterial diversity but decreased soil available nitrogen and phosphorus. Based on the ecological functional analysis, organic farming appeared to enhance nitrogen, sulfur, phosphorus and carbon dynamic cycling in soil, and had the potential to strengthen the soil metabolic ability. While conventional farming increased the intensity of nitrogen cycling, it also enriched several pathogen fungal members. Our results suggest that organic farming exerts more positive influence on soil systems than improved conventional farming. However, further studies about crop growth and health are required to elucidate the applicability of farming systems.

Acknowledgments

This work was financially supported by the National Natural Science Foundation of China (No. 41501259), and the National Key Research and Development Program of China (No. 2016YFD0200804) as well as the Outstanding Team Program of Shanghai Academy of Agricultural Sciences [nong ke chuang 2017(A-03)]. Thanks also to Dr. Lionel Mabit (SWMCN Laboratory of the FAO/IAEA Joint Division) for his helpful advices and comments on our manuscript.

Conflict of interests


The authors have no financial conflicts of interest to declare.

Fig 1.

Figure 1.Venn diagram showing shared and unique genera of soil bacterial and fungal communities in organic farming (OF) and conventional farming (CF). The OTUs were defined at 97% sequence similarity level.
Journal of Microbiology and Biotechnology 2019; 29: 441-453https://doi.org/10.4014/jmb.1809.09007

Fig 2.

Figure 2.Phylogenetic classification of relative abundance of dominant bacterial (A) and fungal (B) phyla in organic farming (OF) and conventional farming (CF).
Journal of Microbiology and Biotechnology 2019; 29: 441-453https://doi.org/10.4014/jmb.1809.09007

Fig 3.

Figure 3.The phylogenetic tree diagram of soil bacterial (A) and fungal (B) communities in organic farming (OF) and conventional farming (CF) based on GraPhlAn. The phylogenetic tree shows the overall sample, from the phylum to the genus (from the inner to the outer ring arranged in sequence). The size of the point represents the average relative abundance of the taxon, and the relative abundance of the first 20 taxa is also identified with letters.
Journal of Microbiology and Biotechnology 2019; 29: 441-453https://doi.org/10.4014/jmb.1809.09007

Fig 4.

Figure 4.Partial Least Squares Discriminant Analysis (PLS-DA) of soil bacterial (A) and fungal (B) communities in organic farming (OF) and conventional farming (CF).
Journal of Microbiology and Biotechnology 2019; 29: 441-453https://doi.org/10.4014/jmb.1809.09007

Fig 5.

Figure 5.The group abundance differences at genus level of soil bacterial (A) and fungal (B) communities in organic farming (OF) and conventional farming (CF) based on Metastats. The top 20 significant differences of group abundance at genus level were listed as separate figures.
Journal of Microbiology and Biotechnology 2019; 29: 441-453https://doi.org/10.4014/jmb.1809.09007

Fig 6.

Figure 6.Redundancy analysis (RDA) of abundance of soil bacterial and fungal (B) associated with environmental variables. The numbers indicate 16 replicates of organic farming (OF) and conventional farming (CF). Environmental variables are indicated by arrows.
Journal of Microbiology and Biotechnology 2019; 29: 441-453https://doi.org/10.4014/jmb.1809.09007

Table 1 . Detailed management of the long-term organic and conventional farming experiment..

System/TreatmentOrganic Farming (OF)Conventional Farming (CF)
Fertilizer typesCommercial organic fertilizeraSynthetic fertilizerb
YearlyTotal nitrogen (TN)555555
Fertilizer Input (kg•ha-1)Total phosphorus (TP) 206213
Total potassium (TK)13593
Plant protection schemeWeed controlMechanicalMechanical and herbicidesc
Disease controlBiological pesticidesChemical pesticidesc
Pest controlBiological pesticidesc and biological control measuresdChemical pesticidesc
Special treatmentsStraw retentione (total amount) Straw retentione (total amount)

a: the commercial organic fertilizer used in OF was measured every year before applied, and pure nitrogen content kept the same amount from 2004 to 2015. The commercial organic fertilizer was derived from livestock manure, and the average nutrients contents were as follows: organic matter content 489 g•kg-1, TN 25.3 g•kg-1, TP 13.4 g•kg-1, TK 12.7 g•kg-1. .

b: the synthetic fertilizers used in CF were urea and bulk blending fertilizer, and N: P2O5: K2O of bulk blending fertilizer was 15: 15: 15..

c: the biological pesticides, herbicides and chemical pesticides used were all in the list of “Recommended categories of pesticides in Shanghai” from 2004-2015. The application of the pesticides and herbicides were in accord with the plant protection opinions of Agro-Technology Extension Center of Chongming..

d: the biological control measures used contained Trichogramma releasing and Vetiver grass planting technology..

e: straw retention was performed by harvester at the same time with harvesting. Straw was cut into about 10 cm-long pieces, and ploughed to 20 cm depth by rotary tiller..


Table 2 . Agrochemical properties of soil samples..

Organic Farming (OF)Conventional Farming (CF)
pH8.41±0.08a8.24±0.11a
Bulk Density (g•cm-3)1.31±0.05a1.33±0.07a
SOC(g•kg-1)15.66±1.08a14.15±0.86b
TN (g•kg-1)1.81±0.10a1.74±0.11a
TP (g•kg-1)1.72±0.12a1.83±0.09a
TK (g•kg-1)12.59±0.71a13.13±0.85a
Available N (mg•kg-1)42.26±3.28b47.94±4.16a
Available P (mg•kg-1)2.49±0.15b3.59±0.21a
Available K (mg•kg-1)127.41±5.25a130.75±6.79a
Soil Salinity (%)0.12±0.01a0.08±0.01b
Cu (mg•kg-1)29.84±2.37a29.93±3.09a
Zn (mg•kg-1)129.42±11.62a116.77±12.13b
Pb (mg•kg-1)20.63±2.10a20.45±3.59a
Cd (mg•kg-1)0.16±0.02a0.14±0.02a
Cr (mg•kg-1)98.60±6.39a98.18±8.04a
Ni (mg•kg-1)35.47±2.36a34.95±3.57a
Fe (g•kg-1)17.81±2.21a19.62±1.79a
Ca (g•kg-1)18.81±2.27a19.32±2.11a
Mg (g•kg-1)8.19±0.80a8.70±0.93a
Hg (mg•kg-1)0.07±0.01b0.13±0.02a
As (mg•kg-1)14.15±2.57a11.26±1.60b

Data in the table are Mean±SE of 8 replicates; Different letters in the same row indicates a significant difference (p< 0.05)..


Table 3 . Estimated OTU richness and diversity indices of the organic and conventional farming fields..

SimpsonChao1ACEShannon
BacteriaOF0.9947±0.0017a1869±157a2382±182a9.19±0.37a
CF0.9917±0.0054b1623±122a2028±191a8.88±0.51b
FungiOF0.9141±0.0287a361±28a371±21a5.09±0.46a
CF0.9354±0.0293a395±33a407±29a5.32±0.37a

Data in the table are Mean±SE of 8 replicates; Different letters in the same row indicates a significant difference (p< 0.05)..


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