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Changes in fungal community and diversity in strawberry rhizosphere soil after 12 years in the greenhouse
Journal of Integrative Agriculture 2019, 18(3): 677–687 Available online at www.sciencedirect.com
ScienceDirect
RESEARCH ARTICLE
Changes in fungal community and diversity in strawberry rhizosphere soil after 12 years in the greenhouse LI Wei-hua, LIU Qi-zhi College of Plant Protection, China Agricultural University, Beijing 100193, P.R.China
Abstract Soil fungi play a very important role in the soil ecological environment. In agricultural production, long-term monoculture and continuous cropping lead to changes in fungal community diversity. However, the effects of long-term monoculture and continuous cropping on strawberry plant health and fungal community diversity have not been elucidated. In this study, using high-throughput sequencing (HTS), we compared the fungal community and diversity of strawberry rhizosphere soil after various durations of continuous cropping (0, 2, 4, 6, 8, 10 and 12 years). The results showed that soil fungal diversity increased with consecutive cropping years. Specifically, the soil-borne disease pathogens Fusarium and Guehomyces were significantly increased after strawberry continuous cropping, and the abundance of nematicidal (Arthrobotrys) fungi decreased from the fourth year of continuous cropping. The results of correlation analysis suggest that these three genera might be key fungi that contribute to the changes in soil properties that occur during continuous cropping. In addition, physicochemical property analysis showed that the soil nutrient content began to decline after the fourth year of continuous cropping. Spearman’s correlation analysis showed that soil pH, available potassium (AK) and ammonium nitrogen (NH4+-N) were the most important edaphic factors leading to contrasting beneficial and pathogenic associations across consecutive strawberry cropping systems. Keywords: fungal community, soil-borne disease, replanted, strawberry rhizosphere soil, agricultural soil ecology
The land area used for agriculture increased nearly 500-
1. Introduction Agriculture is widely recognized as one of the greatest human accomplishments affecting the Earth’s environment.
fold between 1700 and 1980 (Meyer and Turner 1992). Although the amount of cultivated land has increased rapidly, food production still does not meet socioeconomic demands. Therefore, long-term growth of monocultures on the same tracts of land, which has had a negative impact on the soil physicochemical properties needed for the growth of many crops, including soybean, cotton, eggplant and
Received 5 January, 2018 Accepted 15 May, 2018 LI Wei-hua, Mobile: +86-15652567676, E-mail: 2006054074 @163.com; Correspondence LIU Qi-zhi, Mobile: +8615201646529, E-mail: [email protected] © 2019 CAAS. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/). doi: 10.1016/S2095-3119(18)62003-9
strawberry, has been used (Wang Y et al. 2014; Bai et al. 2015; Guo et al. 2015; Li et al. 2016). In addition, long-term continuous cropping usually leads to increased numbers of soil-borne plant pathogens in the soil (Caporaso et al. 2012; Yang et al. 2012). For example, continuous cropping of cucumber can significantly increase fungal communities, especially those of Fusarium (Zhou and Wu 2012). Xiong
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et al. (2015) reported that continuous cropping of vanilla is associated with the accumulation of pathogens (Xiong et al. 2015). Overall, continuous cropping affects the soil in several different ways, causing changes in the soil microbial community structure, deterioration of soil physicochemical properties and changes in the abundance of pathogenic and beneficial microbes (Fuentes et al. 2009; Huang et al. 2013; Ling et al. 2014; Liu et al. 2015; Xiong et al. 2015). These factors, especially physicochemical properties and the abundance of microorganisms, also interact with each other. Microorganisms can promote the cycle of elements, whereas a good physicochemical environment promotes the growth and metabolism of microorganisms (Fuentes et al.et al. 2009). One important factor in continuous cropping involves changes in soil microbial diversity. In the soil environment, microbial communities are also parts of the food web (van Bruggen and Semenov 2000). At the same time, microorganisms play vital roles in many processes, including the carbon, nitrogen, phosphorus and sulfur cycles, as well as providing nutrients to plants (Geisseler et al. 2010; Smith et al. 2011; Karimian et al. 2017; McTee et al. 2017). Plant and animal residues in the soil can be converted to soil organic matter (SOM) by microbial degradation (Nannipieri et al. 2003), and microorganisms produce a variety of enzymes that aid in the direct uptake and indirect absorption of organic nitrogen (Geisseler et al. 2010). Furthermore, soil microbes can serve as indicators of soil quality due to their sensitivity to subtle environmental differences resulting from environmental stresses or natural perturbations (van Bruggen and Semenov 2000; Caporaso et al. 2012). Previous studies have shown that variation in fungal diversity is significantly higher than variation in bacterial diversity after continuous cropping (Xiong et al. 2015). In addition, fungal species cause a proportion of the soil-borne diseases that affect strawberry crops (Maas 1984). The major soil-borne diseases of strawberry caused by fungi are grey mould (Botryotinia fuckeliana) (Braun and Sutton 1988), powdery mildew (Sphaerotheca macularis f. sp. fragariae) (Okayama et al. 2009), anthracnose (Colletotrichum acutatum) (Baroncelli et al. 2015) and fusarium wilt (Fusarium oxysporum f. sp. fragariae) (Henry et al. 2016). These soil-borne diseases can cause failure of the growth of the roots, stems, leaves and fruits of strawberry plants. Conversely, fungi can also benefit plant growth and stimulate metabolic processes by the degradation of organic matter (Wolters 2000), the secretion of antibiotics and the inhibition of nematodes (Song et al. 2017). Fungi are sensitive to environmental changes such as changes in soil pH (Wolters 2000), moisture (Romanowicz et al. 2016) and N availability (Frey et al. 2004). Fungi also have close relationships with plants, particularly in rhizosphere soil.
The rhizosphere, which is the tiny zone of soil that is influenced by root secretions, can contain up to 1011 microbial cells per gram of soil (Egamberdieva et al. 2008) and more than 30 000 prokaryotic species (Mendes et al. 2011). Previous studies have shown that rhizosphere soil contributes to the nutrition and health of plants. A variety of plant-associated microbes are present in rhizosphere soil; these are also referred to as the “second genome” of the plant (Bron et al. 2012). Research has shown that plants are able to shape their rhizosphere microbiomes, suggesting that different plant species host specific microbial communities when grown in the same soil (Berendsen et al. 2012). In addition, when attacked by pathogens or insects, plants are able to recruit protective microorganisms and enhance microbial activity to suppress pathogens in the rhizosphere (Mendes et al. 2013). However, before most soil-borne pathogens can leave the rhizosphere and infect host tissue, they must access their hosts by growing saprophytically or by reproducing sufficiently on their hosts (Hoitink and Boehm 1999). Consequently, the measurement of the microbial community structure and diversity in rhizosphere soil is increasingly being used to assess ecosystem feedback in response to soil environmental gradients and cultivation techniques. During the past century, several methods have been used to analyse microbial communities and diversity. These include microbial cultivation techniques, measurement of the levels of individual phospholipid fatty acids (PLFAs) and fatty acid methyl esters (FAMEs), denaturing gradient gel electrophoresis (DGGE) and identification of terminal restriction fragment length polymorphisms (T-RFLPs). However, each of these methods has specific limitations and shortcomings. For example, microbial cultivation techniques are limited by the fraction of microbes that can be cultured (a maximum of approximately 5%), measurement of PLFAs and FAMEs cannot yield accurate classification information, and DGGE and T-RFLP are not cost-effective in terms of economy and time (Zelles et al. 1992, 1995; de Oliveira et al. 2006; Yin et al. 2010; Mendes et al. 2013). In the present study, we used high-throughput sequencing (HTS) technology to analyse soil microbial community diversity. This approach saves time and is more cost-effective than traditional fingerprinting techniques such as DGGE and measurement of PLFAs, FAMEs, and T-RFLPs. In this study, fungal communities and diversity in strawberry rhizosphere soil were investigated after various durations of continuous cropping. The objectives of the study were: (1) to investigate changes in fungal communities and diversity after different durations of continuous cropping; (2) to identify the time when soil physicochemical properties deteriorate after continuous cropping; (3) to reveal the relationship between fungi and environmental factors; and
LI Wei-hua et al. Journal of Integrative Agriculture 2019, 18(3): 677–687
(4) to identify the key fungi that make continuous cropping problematic.
2. Materials and methods 2.1. Experimental design and soil sampling The experiment was conducted in Haidian District, Beijing, China (40°1´21´´N, 116°16´32´´E). The mean annual rainfall there is 628.9 mm (Li et al. 2016). The characteristics of the soil were as follows: pH, 8.27±0.06; soil total nitrogen (TN), (0.85±0.02) g kg–1; SOM, (10.62±0.03) g kg–1; soil NH 4+-N, (18.75±0.07) mg kg –1; available phosphorus (AP), (15.39±0.04) mg kg–1; and available potash (AK), (47.20±0.12) mg kg–1. The strawberries were planted in greenhouses, all of which were located in the same field, which had a uniform soil type (loam) according to China’s Soil Classification Retrieval System and was maintained under the same management practices. The maximum and minimum temperatures in the greenhouse in December were 26.7 and 10.4°C, respectively. Water was supplied as trickle irrigation. All samples were collected 130 days after planting. The 21 greenhouses in which the plants were cultivated were at the same location and maintained under the same climate conditions and tillage management patterns. The strawberries grown in the greenhouses belonged to a single species (Hongyan). Basal fertilizer, including farm manure (29 985 kg ha–1, organic matter>25%) and NPK fertilizer (300 kg ha–1, N+P2O4+K2O≥45%), was applied before engraftment of the strawberries. Each greenhouse contained 60–80 strawberry beds, each of which was 100 cm in length× 40 cm in width×40 cm in height．The strawberry seedlings were planted in two rows per bed and were spaced 15 cm apart. Each sample consisted of three replicates. Each replicate, consisting of 30 samples, was taken from a different greenhouse. Subsamples of the same replicates of soil samples were taken from different sites in a Z-pattern and were mixed in an aseptic bag. Strawberry roots were acquired from the soil at a depth of 0–20 cm. Each plant was gently pulled from the soil. The soil was gently crushed, and chunks of soil were shaken off; the soil attached to the plant root surfaces, which was defined as rhizosphere soil (Wang M et al. 2014), was collected. The soil samples from year zero and those obtained after continuous cropping for 2, 4, 6, 8, 10 and 12 years were denoted 0_Y, 2_Y, 4_Y, 6_Y, 8_Y, 10_Y and 12_Y, respectively. All samples were collected at the same stage of plant growth and in the same year. After collection of the rhizosphere soil samples, the samples were placed in aseptic bags and transferred to a –80°C freezer in the laboratory. Other soil samples were sieved through a 2-mm mesh sieve and dried at 60°C for physicochemical property analysis.
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2.2. Soil chemical analysis The pH of the soil samples (soil:water=1:5, w/v) was determined using a pH metre with a glass electrode (FE20-Five Easy Plus™, Switzerland) (Qiu et al. 2012). Extraction with 0.5 mol L–1 NaHCO3 was used to determine soil AP according to the molybdenum blue method. TN was measured based on direct combustion using an elemental analyser (Page et al. 1982). Soil NH4+-N was extracted with 2 mol L–1 KCl (soil:KCl=1:10, w/v). The extracts were shaken for 1 h and then filtered; the filtrate was analysed for NH4+-N using a continuous-flow analytical system (Chu and Grogan 2010). Flame photometry was used to analyse the soil AK at a ratio of 5 g of dry soil to 50 mL of 1 mol L–1 ammonium acetate. The extracts were shaken for 30 min, filtered, and subjected to flame photometry (Smith 2010). The SOM was determined using the vitriol acid-potassium dichromate oxidation method (Nelson et al. 1996).
2.3. DNA extraction and PCR conditions Total soil DNA was extracted from 500 mg of fresh soil using a PowerSoil® DNA Isolation Kit (Mobile Biometry, USA). The internal transcribed spacer (ITS) region of the fungal DNA was amplified by PCR (95°C for 2 min followed by 35 cycles of 95°C for 45 s, 50°C for 50 s, and 72°C for 45 s and a final extension at 72°C for 10 min). The reaction was performed in a 50-μL reaction volume consisting of 2 μL (30 ng) of template DNA, 2 μL of ITS1-F forward primer (CTTGGTCATTTAGAGGAAGTAA) and 2 μL of ITS2-R reverse primer (TGCGTTCTTCATCGATGC) (Martin 2011) (both at 10 μmol L–1), 4 μL of dNTPs (2.5 mmol L–1), 5 μL of 10× Pyrobest buffer, 0.3 μL of Pyrobest DNA polymerase (2.5 U μL–1, TaKaRa, Japan), and 34.7 μL of ddH2O. Amplicons were extracted from 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, USA) according to the manufacturer’s instructions. The recovered DNA was quantified using QuantiFluor™-ST (Promega, USA). Purified amplicons were pooled in equimolar samples and paired-end sequenced (PE300) on an Illumina MiSeq PE300 platform according to standard protocols.
2.4. Bioinformatics analysis Noisy amplicon sequences (low-quality sequences) were filtered and removed from the high-quality sequences using the Precluster tool of the Quantitative Insights into Microbial Ecology (QIIME) Software Package (ver. 1.2.1). This quality filtration was performed to remove low-quality sequences. Reads shorter than 110 bp were removed, sequences with homopolymers longer than 10 bp were filtered using a sliding
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window filter score of <20 over 50 bp (Trimmomatic), and truncated reads shorter than 50 bp were discarded. Finally, the overlapped sequences >10 bp in length were assembled on the basis of their overlap sequences; reads that could not be assembled were discarded. Operational taxonomic units (OTUs) with 97% similarity cutoff were clustered using UPARSE (ver. 7.1, http://drive5. com/uparse/), and chimeric sequences were identified and removed using UCHIME. The taxonomy of each ITS gene sequence was analysed by RDP Classifier (http://rdp.cme. msu.edu/) against the ITS database of UNITE (7.0) using a confidence threshold of 70% (Amato et al. 2013).
after 4 years of continuous cropping exhibited the greatest amount of TN, whereas the minimum TN was recorded at 0_Y; the TN values ranged from (1.41±0.04) to (3.6±0.18) g kg–1. NH4+-N decreased significantly (P<0.05) as the duration of continuous cropping increased starting from the sixth year. The SOM content initially increased but then decreased; it ranged from (71.26±1.09) to (29.02±0.11) g kg –1 . The turning point occurred during the fourth year. The amount of AP in the soil samples was significantly higher (P<0.05) after various durations of continuous cropping of strawberries than in the original samples of bulk soil (0_Y). The AK results were the opposite of those obtained for AP.
2.5. Statistical analysis
3.2. Soil fungal community and diversity
The data were analysed by one-way ANOVA followed by Duncan’s multiple range tests using the SPSS Statistical Software Package ver. 20.0 (SPSS Inc., Chicago, IL, USA). Differences at the P≤0.05 level were considered statistically significant. Drawings were created using PRISM (version 7.0) and Mothur (version 1.17.0). The OTUs that reached a 97% nucleotide similarity level were used for alpha diversity (Shannon) and richness (Chao1), and Spearman’s correlation heatmap was generated based on the relative abundance of OTUs using R Package (ver. 2.15; The R Project for Statistical Computing, http:// www.R-project.org). Principal component analysis (PCA) was performed using OTUs for each sample in the Mothur Program.
A total of 1 853 706 clean tag sequences obtained from the 21 soil samples were analysed. The average high-quality sequence length was 243 bp, the maximum length was 528 bp, and the minimum length was 130 bp. The sequences were grouped into 2 623 OTUs using an arbitrary 97% sequence similarity cutoff. Our results showed that 8 phyla, 28 classes, 87 orders, 180 families and 377 genera were present in soil obtained after the seven experimental treatments. All high-quality reads were classified taxonomically (phylum to genus) using the default settings of QIIME. The predominant phyla in all soil samples included Ascomycota (92.07%), Zygomycota (3.09%), Basidiomycota (2.11%), Glomeromycota (0.05%), Chytridiomycota (0.07%) and Blastocladiomycota (0.02%) (Fig. 1-A). The Shannon and Chao1 indexes of the Ascomycota phylum significantly increased (P<0.05) with time, especially in the twelfth year of continuous cropping (Fig. 1-B and C). Taxonomic information at the genus level is shown in Fig. 2-A. Thirty-two genera with sequence abundances greater than 1% were identified. Among them, 22 genera were recognized at the genus level. In all samples, the mean top 10 most abundant identifiable fungal genera were Pseudallescheria (12.44%), Aspergillus (6.98%),
3. Results 3.1. Soil physicochemical properties The physicochemical properties of the soil are shown in Table 1. The pH of the soil decreased significantly as the duration of continuous cropping increased and ranged from 7.46±0.13 to 8.34±0.07; the lowest pH values were recorded in the 12-year-old plots. Compared with bulk soil (0_Y), soil
Table 1 Soil physicochemical properties of strawberry plants after different durations of continuous cropping in the greenhouse1) Treatment2) 0_Y 2_Y 4_Y 6_Y 8_Y 10_Y 12_Y 1)
pH 8.34±0.07 a 8.27±0.05 a 7.99±0.04 b 7.87±0.11 b 7.53±0.11 c 7.46±0.13 c 7.46±0.32 c
TN (g kg–1) 1.41±0.04 f 3.04±0.11 b 3.60±0.18 a 2.93±0.18 b 2.35±0.12 c 2.13±0.10 d 2.00±0.06 d
NH4+-N (mg kg–1) 22.03±1.06 a 21.74±1.52 a 20.97±0.5 a 16.93±0.53 b 15.64±0.38 b 12.43±0.11 c 12.13±0.10 c
SOM (g kg–1) 29.02±0.11 f 55.35±1.09 c 71.26±1.09 a 60.62±0.53 b 31.93±5.54 f 43.48±0.32 d 39.12±1.70 e
AP (mg kg–1) 7.61±5.78 c 23.11±0.91 ab 32.72±0.81 a 28.42±0.53 a 31.92±0.34 a 16.74±12.5 bc 11.26±0.28 c
AK (mg kg–1) 134.52±4.36 a 99.66±1.45 c 107.72±0.64 b 67.87±1.52 d 68.53±1.10 d 58.39±0.81 e 44.18±0.95 f
TN, total nitrogen; NH4+-N, ammonium nitrogen; SOM, soil organic matter; AP, available phosphorus; AK, available potassium. 0_Y, 2 _Y, 4 _Y, 6 _Y, 8 _Y, 10 _Y and 12 _Y represent continuous cropping 0, 2, 4, 6, 8 and 12 years, respectively. Letters following the data (mean±SE) indicate significant differences between samples after different durations of continuous cropping of strawberry (Duncan’s multiple range test, P<0.05).
2)
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A Glomeromycota
unclassified_k_Fungi
Ascomycota
Zygomycota
B
Basidiomycota
6
Others
Shannon index
Chytridiomycota
0.9 0.8
c
b
b
b
3 2
0
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0.4 0.3 0.2 0.1 0
4
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0.7
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Community abundance on phylum level
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P<0.01 F=10.944 b
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8_Y
10_Y
12_Y
1 600 1 400 1 200 1 000 800 600 400 200 0
Different years of continuous cropping
2_Y 4_Y 6_Y 8_Y 10_Y Different years of continuous cropping
P=0.004 F=5.612 bc c
0_Y
b
a
ab
ab
b
12_Y
2_Y 4_Y 6_Y 8_Y 10_Y 12_Y Different years of continuous cropping
Fig. 1 Fungal community at the phylum level. A, proportional distribution of genera with abundance >1%. B, Shannon index of Ascomycota at the operation taxonomic unit (OTU) level. C, Chao1 index of Ascomycota at the OTU level. 0_Y, 2 _Y, 4 _Y, 6 _Y, 8 _Y, 10 _Y and 12 _Y represent continuous cropping 0, 2, 4, 6, 8 and 12 years, respectively. Different letters indicate significant differences between samples after different durations of continuous cropping of strawberry (Duncan’s multiple range test, P<0.05, mean±SE).
B
1.0
5
0.8
4
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0.9
0.7 0.6 0.5
0.3
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0.2 0.1 0
3
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Guehomyces Funneliformis Oliveonia Cephaliophora Unclassified_f_Ceratobasidiaceae Cryptococcus Arthrobotrys Unclassified_c_Sordariomycetes Thermomyces Penicillium Unclassified_o_Trechisporales Olpidiaster Monographella unclassified_f_Glomeraceae Unclassified_p_Ascomycota Gibellulopsis Chaetomium Microascus Myriococcum Morierella Gibberella Unclassified_o_Pezizales Humicola unclassified_c_ Sordariomycetes Acremonium Unclassified_k_Fungi Fusarium Unclassified_f_Chaetomiacee Aspergillus Pseudallescheria Others Unclassified_o_Sordariales Unclassified_f_Gymnoascaceae
P<0.01 F=10.698 c
b
bc
bc
b
b
a
2 1 0
0.4
Chao1
Community abundance at the genus level
A
400 300 200
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2_Y 4_Y 6_Y 8_Y 10_Y 12_Y Different years of continuous cropping
P=0.04 F=5.457 ab c
b
b
bc
ab
a
100 0
0_Y
2_Y 4_Y 6_Y 8_Y 10_Y 12_Y Different years of continuous cropping
Fig. 2 Fungal community at the genus level. A, proportional distribution of genera with abundance >1%. B, Shannon index at the genus level of samples after different durations of continuous cropping. C, Chao1 index at the genus level of samples after different durations of continuous cropping. 0_Y, 2 _Y, 4 _Y, 6 _Y, 8 _Y, 10 _Y and 12 _Y represent continuous cropping 0, 2, 4, 6, 8 and 12 years, respectively. Different letters indicate significant differences after different durations of continuous cropping of strawberry (Duncan’s multiple range test, P<0.05, mean±SE).
Acremonium (4.10%), Fusarium (4.27%), Mortierella (4.24%), Humicola (3.18%), Chaetomium (3.07%), Gibberella (2.39%), Microascus (2.32%) and Myriococcum (2.24%). The Shannon and Chao1 indexes at the genus level increased significantly (P<0.05) with time, especially in the twelfth year of continuous cropping (Fig. 2-B and C).
3.3. Principal component analysis (PCA) of soil fungi Differences and similarities between the microbial communities in the soil samples obtained after different durations of continuous cropping were revealed by PCA at the OTU level. The first and second principal components
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(PCs) explained 32.02 and 30.04%, respectively, of the total variance. The PCA results showed that bulk soil (0_Y) differed from the other samples (2, 4, 6, 8, 10 and 12 years) (Fig. 3).
3.4. The main fungi Of the fungal genera whose relative abundance in the soil samples was greater than 1%, the relative abundance of Guehomyces, Arthrobotrys, Gibellulopsis, Myriococcum, Humicola, Mortierella, Fusarium, Acremonium and Aspergillus differed significantly (P<0.05) after different durations of continuous cropping. These genera belong to the phyla Ascomycota, Zygomycota and Basidiomycota. The highest summed abundance of these nine genera occurred in the second year of continuous cropping (2_Y, 34.97%), and the minimum occurred in the fourth year (4_Y, 15.83%). The relative abundance of Fusarium, in particular, increased significantly (P<0.05) with the duration of continuous cropping (Fig. 4-A). The relative abundance of Humicola, Gibellulopsis and Guehomyces increased significantly after the fourth, sixth and tenth years of continuous cropping, respectively (Fig. 4-C, D and H). On the other hand, the relative abundance of Acremonium and Arthrobotrys decreased significantly (P<0.05) after the second and fourth years, respectively, of continuous cropping (Fig. 4-D and E). The abundance of Aspergillus decreased significantly after the sixth year of continuous cropping; the maximum abundance occurred in that year (6_Y, 13.18%), and the abundance of the genus then gradually decreased (Fig. 4-F). The maximum (7.45%) and minimum (1.94%) Mortierella abundance occurred in the twelfth and sixth years, respectively, of continuous cropping (Fig. 4-G). Myriococcum abundance in the second 20.0
PC 2 (30.04%)
10.0
4_Y 2_Y
0_Y
10_Y 0 12_Y 8_Y
–10.0
6_Y
–20.0 –30.0 –40.0 –10.0
0
20.0 10.0 PC 1 (32.02%)
30.0
Fig. 3 Principal component analysis (PCA) of the fungal community composition of aged strawberry plants of different ages (OTU level). 0_Y, 2 _Y, 4 _Y, 6 _Y, 8 _Y, 10 _Y and 12 _Y represent continuous cropping 0, 2, 4, 6, 8 and 12 years, respectively.
year was significantly higher (P<0.05) than that in the other years (Fig. 4-I).
3.5. Correlations between environmental data and fungal communities To investigate the relationships between the composition of soil fungal communities at the genus level and environmental factors, a Spearman’s correlation heatmap was generated (Fig. 5). The results showed that AK, pH and NH4+-N were negatively correlated with Cryptococcus, Fusarium, Funneliformis, Oliveonia, Gibberella, Humicola and Guehomyces but positively correlated with Arthrobotrys. AP and TN were negatively correlated with Myriococcum and Mortierella, respectively, and SOM was negatively correlated with Monographella, Pseudallescheria, Mortierella, Guehomyces, Gibellulopsis, Aspergillus and Acremonium. Additionally, pH was positively correlated with Microascus, Myriococcum and Acremonium, and NH4+-N was positively correlated with Microascus.
4. Discussion 4.1. Soil physicochemical properties Soil physicochemical properties can affect the abundance and activities of microorganisms and soil-dwelling animals and can indirectly affect crop yield and quality (Xie et al. 2017). In this study, the pH decreased as the strawberry plantation age increased (Table 1). A similar phenomenon was reported for the cultivation of tea plants (Han et al. 2007). Plant growth is affected when the soil pH falls outside a reasonable range (Li et al. 2016). For example, the growth of tea plants is suppressed when the soil pH exceeds 6.5 (Su 2012). Additionally, when the pH is lower than 4.0, consumption of tea plants can jeopardize human health (Alloway 1995). A possible reason for the soil acidification could be that plant roots absorb excess cations such as K+, H+ and NH4+-N (Tang et al. 2013). This result was further confirmed in our study; the concentrations of NH4+-N and K+ were observed to decrease during continuous cropping of strawberry (Table 1). However, the TN, which comprises both anionic and cationic forms of nitrogen, did not decrease as the duration of cultivation increased. With the exception of pH, the trends of all soil physicochemical properties shifted after the fourth year of continuous cropping (Table 1). This result indicates that the ability of the soil to transform elements begins to decline after the fourth year of continuous cropping. To improve strawberry rhizosphere soil, organic fertilizer can be added after four years of continuous cropping.
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15
Relative abundance
0_Y 2_Y 4_Y 6_Y 8_Y 10_Y 12_Y
a
P<0.001 F=20.388 b
5
10 8 6 4 2 0
b
b
b
b
b
b
a b
b 0
1.5
b
b
c 0_Y 2_Y 4_Y 6_Y 8_Y 10_Y12_Y Different years of continuous cropping
b
8 6
a
P<0.001 F=87.203
0
d
d
c d
I
Humicola a
a
a a
b
b
3 2 1 0
b
0_Y 2_Y 4_Y 6_Y 8_Y 10_Y12_Y Different years of continuous cropping
15 10
Gibellulopsis P<0.001 F=16.166
a a b
b b
b
b
0_Y 2_Y 4_Y 6_Y 8_Y 10_Y 12_Y Aspergillus a
P<0.001 F=87.203 b
c c
5
d 0
0_Y 2_Y 4_Y 6_Y 8_Y 10_Y 12_Y
P<0.001 F=8.006
4
F
a
b
4 2
b
Arthrobotrys
0.5 0
b
b
0_Y 2_Y 4_Y 6_Y 8_Y 10_Y 12_Y
1
H
Mortierella
b
1
2
0_Y 2_Y 4_Y 6_Y 8_Y 10_Y 12_Y
P<0.001 F=9.921
a
2
E
Acremonium
a
10
0
G
d
C
Guehomces
P<0.001 F=24.694
Relative abundance
0
d
cd
3
Relative abundance
2
b
bc
4
B b
Relative abundance
6
a
Relative abundance
8
Fusarium
P<0.001 F=12.933
Relative abundance
Relative abundance
D
10
Relative abundance
Relative abundance
A
a
8 6
2 0
d
0_Y 2_Y 4_Y 6_Y 8_Y 10_Y 12_Y
10
4
d
Myriococcum P<0.001 F=8.006
b c
b
b d
cd
0_Y 2_Y 4_Y 6_Y 8_Y 10_Y12_Y Different years of continuous cropping
Fig. 4 Significant differences in the relative abundance of fungi with abundance>1% after different durations of continuous cropping. 0_Y, 2 _Y, 4 _Y, 6 _Y, 8 _Y, 10 _Y and 12 _Y represent continuous cropping 0, 2, 4, 6, 8 and 12 years, respectively. The letters indicate significant differences after different durations of continuous cropping of strawberry (Duncan’s multiple range test, P<0.05, mean±SE).
4.2. Soil fungal diversity To our knowledge, this study represents the first use of HTS technology to analyse changes in soil fungal community structure and diversity during continuous cropping of strawberry. Sequencing of the fungal ITS1 region provided detailed insight into the fungal community patterns that develop in strawberry rhizosphere soil during continuous cropping. Knowledge of the structure and diversity of the fungal community during continuous cropping is essential for sustainable strawberry greenhouse management and production (He et al. 2005). The present study provides evidence that the taxonomic diversity of rhizosphere soil fungi increases as the duration of continuous cropping increases; in another study, fungal diversity was closely associated with continuous cropping in vanilla-growing soil, but bacterial diversity was not significantly changed (Xiong et al. 2015). Our results showed that Ascomycota, Zygomycota and Basidiomycota were the dominant phyla during continuous cropping and that Ascomycota (average 92.07%) was the most dominant phylum (Fig. 2-A). The Shannon and Chao1 indexes for Ascomycota in continuously
cropped rhizosphere soil increased significantly compared with those of 0_Y soil fungi, especially in the twelfth year of continuous cropping (Fig. 2-B and C). Similar results were found at the genus level (Fig. 2-B and C). Fungi play a major ecological role as decomposers, and many species of fungi are present in terrestrial, marine, and freshwater habitats (Miadlikowska et al. 2006). Fungi belonging to the Zygomycota and Basidiomycota were also dominant but were much less prevalent than Ascomycota. Hence, Ascomycota fungi were more reflective of soil conditions. Therefore, increased soil fungal diversity might ameliorate some of the problems associated with continuous cropping. In the present study, fungal diversity was higher in continuously cropped soil than that in 0_Y soil. Thus, we conclude that fungal richness and evenness may increase with the duration of continuous cropping. The top 10 fungal genera found in rhizosphere soil in this study differed from those reported in a previous study of fungal superiority in rhizosphere soil (Nallanchakravarthula et al. 2014). This difference might be due to the use of continuous cropping or the physiochemical characteristics of the soil itself. In the present study, we selected the >1%
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roots. The genus Fusarium contains many pathogenic species; thus, an increase in Fusarium abundance is likely to lead to plant disease. Guehomyces is often used in the degradation of industrial waste products; it can degrade lignin-containing wastes through its ligninase and Mnperoxidase activities (Sláviková et al. 2002). Humicola produces cellulose acetate deacetylase; the biodegradative activity of this enzyme in disposal environments (compost, wastewater, and soil) decreases as the degree of substitution increases (Olaru et al. 2004; Puls et al. 2004, 2011), resulting in an increase in the levels of lignin, cellulose and hemicellulose in the soil. Increased levels of these compounds generally lead to an increase in the number of nematodes that feed on crop plants. In contrast, the relative abundance of Acremonium and Artrobotrys declined significantly (P<0.05) after continuous cropping (Fig. 4-D and E). Arthrobotrys has been shown to kill 85% of nematodes within 6 h of contact (Song et al. 2017); in the present study, the abundance of Arthrobotrys decreased significantly after four years of continuous cropping (Fig. 4). Hence, many plant nematodes, including Meloidogyne, Tylenchus and Pratylenchus, might survive because the pathogen density
most abundant species and used these to analyse the fungal community patterns that are presumably linked to the adverse effects of continuous cropping at the genus level (Fig. 2-A). The results showed that among 32 genera, nine genera (Guehomyces, Arthrobotrys, Gibellulopsis, Myriococcum, Humicola, Mortierella, Fusarium, Acremonium and Aspergillus) displayed significant differences (P<0.05) after continuous cropping (Figs. 2-A and 4). The functions of these nine fungi mainly include the production of soilborne diseases, defence and decomposition. Most soilborne diseases are caused by soil fungi such as Fusarium oxysporum (Gullino et al. 2002), Gibellulopsis (Zhou et al. 2017), Pyrenochaeta lycopersici (Campbell et al. 1982) and Verticillium spp. (Harris 1990). Increases in the number of soil-borne disease pathogens can aggravate the effects of continuous cropping. In particular, the relative abundances of Fusarium, Guehomyces, and Humicola significantly increased (P<0.05) after continuous cropping (Fig. 4-A, B and H). Fusarium proliferatum can infect garlic roots and produce mycotoxins during crop growth (Gálvez et al. 2017). Fusarium graminearum and Gibberella zeae cause stalk rot in maize and infect plants by directly penetrating seedling
–0.084
–0.016
–0.079
–0.313
–0.424
–0.304
Penicillium
–0.125
–0.276
–0.252
–0.022
–0.273
–0.466
Monographella
–0.087
–0.035
–0.123
–0.075
–0.354
–0.46
Pseudallescheria
–0.087
–0.069
–0.126
–0.003
–0.318
–0.416
Chaetomium
–0.659
–0.78
–0.757
–0.024
–0.324
–0.327
Cryptococcus
–0.679
–0.653
–0.691
–0.061
–0.17
–0.239
Fusarium
–0.612
–0.692
–0.691
–0.092
–0.203
–0.192
Funneliformis
–0.581
–0.562
–0.542
–0.096
–0.049
–0.101
Olveonia
–0.523
–0.481
–0.517
–0.097
–0.198
–0.294
Gibberella
–0.525
–0.616
–0.596
0.153
–0.198
–0.361
Humicola
–0.296
–0.418
–0.391
–0.223
–0.528
–0.683
Mortierella
–0.521
–0.629
–0.64
–0.005
–0.396
–0.473
Guehomyces
–0.338
–0.493
–0.438
–0.034
–0.428
–0.570
Gibellulopsis
–0.362
–0.388
–0.444
–0.006
–0.348
–0.369
Cephaliophora
–0.153
0.034
0.023
0.071
0.292
0.422
Olpidiaster
0.425
0.595
0.474
0.047
0.218
0.081
Arthrobotrys
0.751
0.815
0.799
–0.096
–0.055
–0.014
Microascus
0.242
0.506
0.384
–0.579
–0.301
–0.168
Myriococcum
0.186
0.212
0.194
–0.165
–0.327
–0.527
Aspergillus
0.344
0.468
0.390
–0.130
–0.240
–0.453
Acremonium
0.360
0.402
0.309
–0.081
–0.180
–0.370
Thermomyces
AK
pH
NH4+-N
AP
TN
SOM
0.8 0.6 0.4 0.2 0.0 –0.2 –0.4 –0.6
Fig. 5 Spearman’s correlation heatmap based on population abundance and environment variables at the genus level for genera with abundance>1%. The phylogenetic tree was calculated using the neighbour-joining method, and the relationship among the environmental variables was determined using the Bray distance and the complete clustering method. The heatmap plot depicts the correlation between environmental variables (AK, rapidly available potassium; NH4+-N, ammonium nitrogen; AP, rapidly available phosphorus; TN, total nitrogen; SOM, soil organic matter) and fungal genera with abundance>1%. Red indicates positive correlations; green indicates negative correlations.
LI Wei-hua et al. Journal of Integrative Agriculture 2019, 18(3): 677–687
is low and food availability is increased. In addition, fungal endophyte Acremonium species are important in plant disease control (Redman et al. 1999). In particular, the content of Fusarium, Guehomyces, Humicola, Acremonium and Artrobotrys changed significantly after the fourth year of continuous cropping. Previous research has shown that soil fertility and the presence of microorganisms are closely related to crop yields (Pešaković et al. 2013). These changes in fungal populations might lead to decreased soil health and reduced crop yields.
4.3. Correlations between environmental data and fungal communities Previous studies have reported an association between soil physicochemical properties and the metabolism of microorganisms (Wolters 2000; Tang et al. 2013; Xie et al. 2017). Similarly, this study showed that AK, pH and NH4+-N significantly influence soil fungal diversity according to Spearman’s correlation analysis (Fig. 5). In addition, Fusarium, Guehomyces and Arthrobotrys were associated with soil physicochemical properties, and the fungi of these genera differed significantly in abundance (abundance >1%). Hence, Fusarium, Guehomyces and Arthrobotrys might be the key fungal species associated with continuous cropping.
5. Conclusion This study showed that the soil environment changes significantly after continuous cropping of strawberry. With the changing trend in soil physicochemical properties, the soil nutrient content began to decline after the fourth year of continuous cropping. Continuous cropping reduced the AK, pH and NH4+-N content of the soil and altered the fungal community in the soil environment. The results suggested that Fusarium, Guehomyces and Arthrobotrys might be the key fungi associated with continuous cropping. Fungal diversity and evenness increased significantly in the twelfth year of continuous cropping. Moreover, the relative abundance of plant pathogenic fungi of the genus Fusarium gradually increased as the duration of continuous cropping increased. Determining the fungal mechanisms that affect plant growth is among the future challenges of agricultural ecological research. However, exploring the complexity of the interactions between plant roots and fungi within the soil environment will be particularly difficult.
Acknowledgements The present study was funded by the National Science and Technology Support Program of China (2014BAD16B07).
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Executive Editor-in-Chief ZHANG Wei-li Managing editor SUN Lu-juan
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RESEARCH ARTICLE
Changes in fungal community and diversity in strawberry rhizosphere soil after 12 years in the greenhouse LI Wei-hua, LIU Qi-zhi College of Plant Protection, China Agricultural University, Beijing 100193, P.R.China
Abstract Soil fungi play a very important role in the soil ecological environment. In agricultural production, long-term monoculture and continuous cropping lead to changes in fungal community diversity. However, the effects of long-term monoculture and continuous cropping on strawberry plant health and fungal community diversity have not been elucidated. In this study, using high-throughput sequencing (HTS), we compared the fungal community and diversity of strawberry rhizosphere soil after various durations of continuous cropping (0, 2, 4, 6, 8, 10 and 12 years). The results showed that soil fungal diversity increased with consecutive cropping years. Specifically, the soil-borne disease pathogens Fusarium and Guehomyces were significantly increased after strawberry continuous cropping, and the abundance of nematicidal (Arthrobotrys) fungi decreased from the fourth year of continuous cropping. The results of correlation analysis suggest that these three genera might be key fungi that contribute to the changes in soil properties that occur during continuous cropping. In addition, physicochemical property analysis showed that the soil nutrient content began to decline after the fourth year of continuous cropping. Spearman’s correlation analysis showed that soil pH, available potassium (AK) and ammonium nitrogen (NH4+-N) were the most important edaphic factors leading to contrasting beneficial and pathogenic associations across consecutive strawberry cropping systems. Keywords: fungal community, soil-borne disease, replanted, strawberry rhizosphere soil, agricultural soil ecology
The land area used for agriculture increased nearly 500-
1. Introduction Agriculture is widely recognized as one of the greatest human accomplishments affecting the Earth’s environment.
fold between 1700 and 1980 (Meyer and Turner 1992). Although the amount of cultivated land has increased rapidly, food production still does not meet socioeconomic demands. Therefore, long-term growth of monocultures on the same tracts of land, which has had a negative impact on the soil physicochemical properties needed for the growth of many crops, including soybean, cotton, eggplant and
Received 5 January, 2018 Accepted 15 May, 2018 LI Wei-hua, Mobile: +86-15652567676, E-mail: 2006054074 @163.com; Correspondence LIU Qi-zhi, Mobile: +8615201646529, E-mail: [email protected] © 2019 CAAS. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/). doi: 10.1016/S2095-3119(18)62003-9
strawberry, has been used (Wang Y et al. 2014; Bai et al. 2015; Guo et al. 2015; Li et al. 2016). In addition, long-term continuous cropping usually leads to increased numbers of soil-borne plant pathogens in the soil (Caporaso et al. 2012; Yang et al. 2012). For example, continuous cropping of cucumber can significantly increase fungal communities, especially those of Fusarium (Zhou and Wu 2012). Xiong
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et al. (2015) reported that continuous cropping of vanilla is associated with the accumulation of pathogens (Xiong et al. 2015). Overall, continuous cropping affects the soil in several different ways, causing changes in the soil microbial community structure, deterioration of soil physicochemical properties and changes in the abundance of pathogenic and beneficial microbes (Fuentes et al. 2009; Huang et al. 2013; Ling et al. 2014; Liu et al. 2015; Xiong et al. 2015). These factors, especially physicochemical properties and the abundance of microorganisms, also interact with each other. Microorganisms can promote the cycle of elements, whereas a good physicochemical environment promotes the growth and metabolism of microorganisms (Fuentes et al.et al. 2009). One important factor in continuous cropping involves changes in soil microbial diversity. In the soil environment, microbial communities are also parts of the food web (van Bruggen and Semenov 2000). At the same time, microorganisms play vital roles in many processes, including the carbon, nitrogen, phosphorus and sulfur cycles, as well as providing nutrients to plants (Geisseler et al. 2010; Smith et al. 2011; Karimian et al. 2017; McTee et al. 2017). Plant and animal residues in the soil can be converted to soil organic matter (SOM) by microbial degradation (Nannipieri et al. 2003), and microorganisms produce a variety of enzymes that aid in the direct uptake and indirect absorption of organic nitrogen (Geisseler et al. 2010). Furthermore, soil microbes can serve as indicators of soil quality due to their sensitivity to subtle environmental differences resulting from environmental stresses or natural perturbations (van Bruggen and Semenov 2000; Caporaso et al. 2012). Previous studies have shown that variation in fungal diversity is significantly higher than variation in bacterial diversity after continuous cropping (Xiong et al. 2015). In addition, fungal species cause a proportion of the soil-borne diseases that affect strawberry crops (Maas 1984). The major soil-borne diseases of strawberry caused by fungi are grey mould (Botryotinia fuckeliana) (Braun and Sutton 1988), powdery mildew (Sphaerotheca macularis f. sp. fragariae) (Okayama et al. 2009), anthracnose (Colletotrichum acutatum) (Baroncelli et al. 2015) and fusarium wilt (Fusarium oxysporum f. sp. fragariae) (Henry et al. 2016). These soil-borne diseases can cause failure of the growth of the roots, stems, leaves and fruits of strawberry plants. Conversely, fungi can also benefit plant growth and stimulate metabolic processes by the degradation of organic matter (Wolters 2000), the secretion of antibiotics and the inhibition of nematodes (Song et al. 2017). Fungi are sensitive to environmental changes such as changes in soil pH (Wolters 2000), moisture (Romanowicz et al. 2016) and N availability (Frey et al. 2004). Fungi also have close relationships with plants, particularly in rhizosphere soil.
The rhizosphere, which is the tiny zone of soil that is influenced by root secretions, can contain up to 1011 microbial cells per gram of soil (Egamberdieva et al. 2008) and more than 30 000 prokaryotic species (Mendes et al. 2011). Previous studies have shown that rhizosphere soil contributes to the nutrition and health of plants. A variety of plant-associated microbes are present in rhizosphere soil; these are also referred to as the “second genome” of the plant (Bron et al. 2012). Research has shown that plants are able to shape their rhizosphere microbiomes, suggesting that different plant species host specific microbial communities when grown in the same soil (Berendsen et al. 2012). In addition, when attacked by pathogens or insects, plants are able to recruit protective microorganisms and enhance microbial activity to suppress pathogens in the rhizosphere (Mendes et al. 2013). However, before most soil-borne pathogens can leave the rhizosphere and infect host tissue, they must access their hosts by growing saprophytically or by reproducing sufficiently on their hosts (Hoitink and Boehm 1999). Consequently, the measurement of the microbial community structure and diversity in rhizosphere soil is increasingly being used to assess ecosystem feedback in response to soil environmental gradients and cultivation techniques. During the past century, several methods have been used to analyse microbial communities and diversity. These include microbial cultivation techniques, measurement of the levels of individual phospholipid fatty acids (PLFAs) and fatty acid methyl esters (FAMEs), denaturing gradient gel electrophoresis (DGGE) and identification of terminal restriction fragment length polymorphisms (T-RFLPs). However, each of these methods has specific limitations and shortcomings. For example, microbial cultivation techniques are limited by the fraction of microbes that can be cultured (a maximum of approximately 5%), measurement of PLFAs and FAMEs cannot yield accurate classification information, and DGGE and T-RFLP are not cost-effective in terms of economy and time (Zelles et al. 1992, 1995; de Oliveira et al. 2006; Yin et al. 2010; Mendes et al. 2013). In the present study, we used high-throughput sequencing (HTS) technology to analyse soil microbial community diversity. This approach saves time and is more cost-effective than traditional fingerprinting techniques such as DGGE and measurement of PLFAs, FAMEs, and T-RFLPs. In this study, fungal communities and diversity in strawberry rhizosphere soil were investigated after various durations of continuous cropping. The objectives of the study were: (1) to investigate changes in fungal communities and diversity after different durations of continuous cropping; (2) to identify the time when soil physicochemical properties deteriorate after continuous cropping; (3) to reveal the relationship between fungi and environmental factors; and
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(4) to identify the key fungi that make continuous cropping problematic.
2. Materials and methods 2.1. Experimental design and soil sampling The experiment was conducted in Haidian District, Beijing, China (40°1´21´´N, 116°16´32´´E). The mean annual rainfall there is 628.9 mm (Li et al. 2016). The characteristics of the soil were as follows: pH, 8.27±0.06; soil total nitrogen (TN), (0.85±0.02) g kg–1; SOM, (10.62±0.03) g kg–1; soil NH 4+-N, (18.75±0.07) mg kg –1; available phosphorus (AP), (15.39±0.04) mg kg–1; and available potash (AK), (47.20±0.12) mg kg–1. The strawberries were planted in greenhouses, all of which were located in the same field, which had a uniform soil type (loam) according to China’s Soil Classification Retrieval System and was maintained under the same management practices. The maximum and minimum temperatures in the greenhouse in December were 26.7 and 10.4°C, respectively. Water was supplied as trickle irrigation. All samples were collected 130 days after planting. The 21 greenhouses in which the plants were cultivated were at the same location and maintained under the same climate conditions and tillage management patterns. The strawberries grown in the greenhouses belonged to a single species (Hongyan). Basal fertilizer, including farm manure (29 985 kg ha–1, organic matter>25%) and NPK fertilizer (300 kg ha–1, N+P2O4+K2O≥45%), was applied before engraftment of the strawberries. Each greenhouse contained 60–80 strawberry beds, each of which was 100 cm in length× 40 cm in width×40 cm in height．The strawberry seedlings were planted in two rows per bed and were spaced 15 cm apart. Each sample consisted of three replicates. Each replicate, consisting of 30 samples, was taken from a different greenhouse. Subsamples of the same replicates of soil samples were taken from different sites in a Z-pattern and were mixed in an aseptic bag. Strawberry roots were acquired from the soil at a depth of 0–20 cm. Each plant was gently pulled from the soil. The soil was gently crushed, and chunks of soil were shaken off; the soil attached to the plant root surfaces, which was defined as rhizosphere soil (Wang M et al. 2014), was collected. The soil samples from year zero and those obtained after continuous cropping for 2, 4, 6, 8, 10 and 12 years were denoted 0_Y, 2_Y, 4_Y, 6_Y, 8_Y, 10_Y and 12_Y, respectively. All samples were collected at the same stage of plant growth and in the same year. After collection of the rhizosphere soil samples, the samples were placed in aseptic bags and transferred to a –80°C freezer in the laboratory. Other soil samples were sieved through a 2-mm mesh sieve and dried at 60°C for physicochemical property analysis.
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2.2. Soil chemical analysis The pH of the soil samples (soil:water=1:5, w/v) was determined using a pH metre with a glass electrode (FE20-Five Easy Plus™, Switzerland) (Qiu et al. 2012). Extraction with 0.5 mol L–1 NaHCO3 was used to determine soil AP according to the molybdenum blue method. TN was measured based on direct combustion using an elemental analyser (Page et al. 1982). Soil NH4+-N was extracted with 2 mol L–1 KCl (soil:KCl=1:10, w/v). The extracts were shaken for 1 h and then filtered; the filtrate was analysed for NH4+-N using a continuous-flow analytical system (Chu and Grogan 2010). Flame photometry was used to analyse the soil AK at a ratio of 5 g of dry soil to 50 mL of 1 mol L–1 ammonium acetate. The extracts were shaken for 30 min, filtered, and subjected to flame photometry (Smith 2010). The SOM was determined using the vitriol acid-potassium dichromate oxidation method (Nelson et al. 1996).
2.3. DNA extraction and PCR conditions Total soil DNA was extracted from 500 mg of fresh soil using a PowerSoil® DNA Isolation Kit (Mobile Biometry, USA). The internal transcribed spacer (ITS) region of the fungal DNA was amplified by PCR (95°C for 2 min followed by 35 cycles of 95°C for 45 s, 50°C for 50 s, and 72°C for 45 s and a final extension at 72°C for 10 min). The reaction was performed in a 50-μL reaction volume consisting of 2 μL (30 ng) of template DNA, 2 μL of ITS1-F forward primer (CTTGGTCATTTAGAGGAAGTAA) and 2 μL of ITS2-R reverse primer (TGCGTTCTTCATCGATGC) (Martin 2011) (both at 10 μmol L–1), 4 μL of dNTPs (2.5 mmol L–1), 5 μL of 10× Pyrobest buffer, 0.3 μL of Pyrobest DNA polymerase (2.5 U μL–1, TaKaRa, Japan), and 34.7 μL of ddH2O. Amplicons were extracted from 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, USA) according to the manufacturer’s instructions. The recovered DNA was quantified using QuantiFluor™-ST (Promega, USA). Purified amplicons were pooled in equimolar samples and paired-end sequenced (PE300) on an Illumina MiSeq PE300 platform according to standard protocols.
2.4. Bioinformatics analysis Noisy amplicon sequences (low-quality sequences) were filtered and removed from the high-quality sequences using the Precluster tool of the Quantitative Insights into Microbial Ecology (QIIME) Software Package (ver. 1.2.1). This quality filtration was performed to remove low-quality sequences. Reads shorter than 110 bp were removed, sequences with homopolymers longer than 10 bp were filtered using a sliding
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window filter score of <20 over 50 bp (Trimmomatic), and truncated reads shorter than 50 bp were discarded. Finally, the overlapped sequences >10 bp in length were assembled on the basis of their overlap sequences; reads that could not be assembled were discarded. Operational taxonomic units (OTUs) with 97% similarity cutoff were clustered using UPARSE (ver. 7.1, http://drive5. com/uparse/), and chimeric sequences were identified and removed using UCHIME. The taxonomy of each ITS gene sequence was analysed by RDP Classifier (http://rdp.cme. msu.edu/) against the ITS database of UNITE (7.0) using a confidence threshold of 70% (Amato et al. 2013).
after 4 years of continuous cropping exhibited the greatest amount of TN, whereas the minimum TN was recorded at 0_Y; the TN values ranged from (1.41±0.04) to (3.6±0.18) g kg–1. NH4+-N decreased significantly (P<0.05) as the duration of continuous cropping increased starting from the sixth year. The SOM content initially increased but then decreased; it ranged from (71.26±1.09) to (29.02±0.11) g kg –1 . The turning point occurred during the fourth year. The amount of AP in the soil samples was significantly higher (P<0.05) after various durations of continuous cropping of strawberries than in the original samples of bulk soil (0_Y). The AK results were the opposite of those obtained for AP.
2.5. Statistical analysis
3.2. Soil fungal community and diversity
The data were analysed by one-way ANOVA followed by Duncan’s multiple range tests using the SPSS Statistical Software Package ver. 20.0 (SPSS Inc., Chicago, IL, USA). Differences at the P≤0.05 level were considered statistically significant. Drawings were created using PRISM (version 7.0) and Mothur (version 1.17.0). The OTUs that reached a 97% nucleotide similarity level were used for alpha diversity (Shannon) and richness (Chao1), and Spearman’s correlation heatmap was generated based on the relative abundance of OTUs using R Package (ver. 2.15; The R Project for Statistical Computing, http:// www.R-project.org). Principal component analysis (PCA) was performed using OTUs for each sample in the Mothur Program.
A total of 1 853 706 clean tag sequences obtained from the 21 soil samples were analysed. The average high-quality sequence length was 243 bp, the maximum length was 528 bp, and the minimum length was 130 bp. The sequences were grouped into 2 623 OTUs using an arbitrary 97% sequence similarity cutoff. Our results showed that 8 phyla, 28 classes, 87 orders, 180 families and 377 genera were present in soil obtained after the seven experimental treatments. All high-quality reads were classified taxonomically (phylum to genus) using the default settings of QIIME. The predominant phyla in all soil samples included Ascomycota (92.07%), Zygomycota (3.09%), Basidiomycota (2.11%), Glomeromycota (0.05%), Chytridiomycota (0.07%) and Blastocladiomycota (0.02%) (Fig. 1-A). The Shannon and Chao1 indexes of the Ascomycota phylum significantly increased (P<0.05) with time, especially in the twelfth year of continuous cropping (Fig. 1-B and C). Taxonomic information at the genus level is shown in Fig. 2-A. Thirty-two genera with sequence abundances greater than 1% were identified. Among them, 22 genera were recognized at the genus level. In all samples, the mean top 10 most abundant identifiable fungal genera were Pseudallescheria (12.44%), Aspergillus (6.98%),
3. Results 3.1. Soil physicochemical properties The physicochemical properties of the soil are shown in Table 1. The pH of the soil decreased significantly as the duration of continuous cropping increased and ranged from 7.46±0.13 to 8.34±0.07; the lowest pH values were recorded in the 12-year-old plots. Compared with bulk soil (0_Y), soil
Table 1 Soil physicochemical properties of strawberry plants after different durations of continuous cropping in the greenhouse1) Treatment2) 0_Y 2_Y 4_Y 6_Y 8_Y 10_Y 12_Y 1)
pH 8.34±0.07 a 8.27±0.05 a 7.99±0.04 b 7.87±0.11 b 7.53±0.11 c 7.46±0.13 c 7.46±0.32 c
TN (g kg–1) 1.41±0.04 f 3.04±0.11 b 3.60±0.18 a 2.93±0.18 b 2.35±0.12 c 2.13±0.10 d 2.00±0.06 d
NH4+-N (mg kg–1) 22.03±1.06 a 21.74±1.52 a 20.97±0.5 a 16.93±0.53 b 15.64±0.38 b 12.43±0.11 c 12.13±0.10 c
SOM (g kg–1) 29.02±0.11 f 55.35±1.09 c 71.26±1.09 a 60.62±0.53 b 31.93±5.54 f 43.48±0.32 d 39.12±1.70 e
AP (mg kg–1) 7.61±5.78 c 23.11±0.91 ab 32.72±0.81 a 28.42±0.53 a 31.92±0.34 a 16.74±12.5 bc 11.26±0.28 c
AK (mg kg–1) 134.52±4.36 a 99.66±1.45 c 107.72±0.64 b 67.87±1.52 d 68.53±1.10 d 58.39±0.81 e 44.18±0.95 f
TN, total nitrogen; NH4+-N, ammonium nitrogen; SOM, soil organic matter; AP, available phosphorus; AK, available potassium. 0_Y, 2 _Y, 4 _Y, 6 _Y, 8 _Y, 10 _Y and 12 _Y represent continuous cropping 0, 2, 4, 6, 8 and 12 years, respectively. Letters following the data (mean±SE) indicate significant differences between samples after different durations of continuous cropping of strawberry (Duncan’s multiple range test, P<0.05).
2)
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A Glomeromycota
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Fig. 1 Fungal community at the phylum level. A, proportional distribution of genera with abundance >1%. B, Shannon index of Ascomycota at the operation taxonomic unit (OTU) level. C, Chao1 index of Ascomycota at the OTU level. 0_Y, 2 _Y, 4 _Y, 6 _Y, 8 _Y, 10 _Y and 12 _Y represent continuous cropping 0, 2, 4, 6, 8 and 12 years, respectively. Different letters indicate significant differences between samples after different durations of continuous cropping of strawberry (Duncan’s multiple range test, P<0.05, mean±SE).
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Guehomyces Funneliformis Oliveonia Cephaliophora Unclassified_f_Ceratobasidiaceae Cryptococcus Arthrobotrys Unclassified_c_Sordariomycetes Thermomyces Penicillium Unclassified_o_Trechisporales Olpidiaster Monographella unclassified_f_Glomeraceae Unclassified_p_Ascomycota Gibellulopsis Chaetomium Microascus Myriococcum Morierella Gibberella Unclassified_o_Pezizales Humicola unclassified_c_ Sordariomycetes Acremonium Unclassified_k_Fungi Fusarium Unclassified_f_Chaetomiacee Aspergillus Pseudallescheria Others Unclassified_o_Sordariales Unclassified_f_Gymnoascaceae
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Fig. 2 Fungal community at the genus level. A, proportional distribution of genera with abundance >1%. B, Shannon index at the genus level of samples after different durations of continuous cropping. C, Chao1 index at the genus level of samples after different durations of continuous cropping. 0_Y, 2 _Y, 4 _Y, 6 _Y, 8 _Y, 10 _Y and 12 _Y represent continuous cropping 0, 2, 4, 6, 8 and 12 years, respectively. Different letters indicate significant differences after different durations of continuous cropping of strawberry (Duncan’s multiple range test, P<0.05, mean±SE).
Acremonium (4.10%), Fusarium (4.27%), Mortierella (4.24%), Humicola (3.18%), Chaetomium (3.07%), Gibberella (2.39%), Microascus (2.32%) and Myriococcum (2.24%). The Shannon and Chao1 indexes at the genus level increased significantly (P<0.05) with time, especially in the twelfth year of continuous cropping (Fig. 2-B and C).
3.3. Principal component analysis (PCA) of soil fungi Differences and similarities between the microbial communities in the soil samples obtained after different durations of continuous cropping were revealed by PCA at the OTU level. The first and second principal components
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(PCs) explained 32.02 and 30.04%, respectively, of the total variance. The PCA results showed that bulk soil (0_Y) differed from the other samples (2, 4, 6, 8, 10 and 12 years) (Fig. 3).
3.4. The main fungi Of the fungal genera whose relative abundance in the soil samples was greater than 1%, the relative abundance of Guehomyces, Arthrobotrys, Gibellulopsis, Myriococcum, Humicola, Mortierella, Fusarium, Acremonium and Aspergillus differed significantly (P<0.05) after different durations of continuous cropping. These genera belong to the phyla Ascomycota, Zygomycota and Basidiomycota. The highest summed abundance of these nine genera occurred in the second year of continuous cropping (2_Y, 34.97%), and the minimum occurred in the fourth year (4_Y, 15.83%). The relative abundance of Fusarium, in particular, increased significantly (P<0.05) with the duration of continuous cropping (Fig. 4-A). The relative abundance of Humicola, Gibellulopsis and Guehomyces increased significantly after the fourth, sixth and tenth years of continuous cropping, respectively (Fig. 4-C, D and H). On the other hand, the relative abundance of Acremonium and Arthrobotrys decreased significantly (P<0.05) after the second and fourth years, respectively, of continuous cropping (Fig. 4-D and E). The abundance of Aspergillus decreased significantly after the sixth year of continuous cropping; the maximum abundance occurred in that year (6_Y, 13.18%), and the abundance of the genus then gradually decreased (Fig. 4-F). The maximum (7.45%) and minimum (1.94%) Mortierella abundance occurred in the twelfth and sixth years, respectively, of continuous cropping (Fig. 4-G). Myriococcum abundance in the second 20.0
PC 2 (30.04%)
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Fig. 3 Principal component analysis (PCA) of the fungal community composition of aged strawberry plants of different ages (OTU level). 0_Y, 2 _Y, 4 _Y, 6 _Y, 8 _Y, 10 _Y and 12 _Y represent continuous cropping 0, 2, 4, 6, 8 and 12 years, respectively.
year was significantly higher (P<0.05) than that in the other years (Fig. 4-I).
3.5. Correlations between environmental data and fungal communities To investigate the relationships between the composition of soil fungal communities at the genus level and environmental factors, a Spearman’s correlation heatmap was generated (Fig. 5). The results showed that AK, pH and NH4+-N were negatively correlated with Cryptococcus, Fusarium, Funneliformis, Oliveonia, Gibberella, Humicola and Guehomyces but positively correlated with Arthrobotrys. AP and TN were negatively correlated with Myriococcum and Mortierella, respectively, and SOM was negatively correlated with Monographella, Pseudallescheria, Mortierella, Guehomyces, Gibellulopsis, Aspergillus and Acremonium. Additionally, pH was positively correlated with Microascus, Myriococcum and Acremonium, and NH4+-N was positively correlated with Microascus.
4. Discussion 4.1. Soil physicochemical properties Soil physicochemical properties can affect the abundance and activities of microorganisms and soil-dwelling animals and can indirectly affect crop yield and quality (Xie et al. 2017). In this study, the pH decreased as the strawberry plantation age increased (Table 1). A similar phenomenon was reported for the cultivation of tea plants (Han et al. 2007). Plant growth is affected when the soil pH falls outside a reasonable range (Li et al. 2016). For example, the growth of tea plants is suppressed when the soil pH exceeds 6.5 (Su 2012). Additionally, when the pH is lower than 4.0, consumption of tea plants can jeopardize human health (Alloway 1995). A possible reason for the soil acidification could be that plant roots absorb excess cations such as K+, H+ and NH4+-N (Tang et al. 2013). This result was further confirmed in our study; the concentrations of NH4+-N and K+ were observed to decrease during continuous cropping of strawberry (Table 1). However, the TN, which comprises both anionic and cationic forms of nitrogen, did not decrease as the duration of cultivation increased. With the exception of pH, the trends of all soil physicochemical properties shifted after the fourth year of continuous cropping (Table 1). This result indicates that the ability of the soil to transform elements begins to decline after the fourth year of continuous cropping. To improve strawberry rhizosphere soil, organic fertilizer can be added after four years of continuous cropping.
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Fig. 4 Significant differences in the relative abundance of fungi with abundance>1% after different durations of continuous cropping. 0_Y, 2 _Y, 4 _Y, 6 _Y, 8 _Y, 10 _Y and 12 _Y represent continuous cropping 0, 2, 4, 6, 8 and 12 years, respectively. The letters indicate significant differences after different durations of continuous cropping of strawberry (Duncan’s multiple range test, P<0.05, mean±SE).
4.2. Soil fungal diversity To our knowledge, this study represents the first use of HTS technology to analyse changes in soil fungal community structure and diversity during continuous cropping of strawberry. Sequencing of the fungal ITS1 region provided detailed insight into the fungal community patterns that develop in strawberry rhizosphere soil during continuous cropping. Knowledge of the structure and diversity of the fungal community during continuous cropping is essential for sustainable strawberry greenhouse management and production (He et al. 2005). The present study provides evidence that the taxonomic diversity of rhizosphere soil fungi increases as the duration of continuous cropping increases; in another study, fungal diversity was closely associated with continuous cropping in vanilla-growing soil, but bacterial diversity was not significantly changed (Xiong et al. 2015). Our results showed that Ascomycota, Zygomycota and Basidiomycota were the dominant phyla during continuous cropping and that Ascomycota (average 92.07%) was the most dominant phylum (Fig. 2-A). The Shannon and Chao1 indexes for Ascomycota in continuously
cropped rhizosphere soil increased significantly compared with those of 0_Y soil fungi, especially in the twelfth year of continuous cropping (Fig. 2-B and C). Similar results were found at the genus level (Fig. 2-B and C). Fungi play a major ecological role as decomposers, and many species of fungi are present in terrestrial, marine, and freshwater habitats (Miadlikowska et al. 2006). Fungi belonging to the Zygomycota and Basidiomycota were also dominant but were much less prevalent than Ascomycota. Hence, Ascomycota fungi were more reflective of soil conditions. Therefore, increased soil fungal diversity might ameliorate some of the problems associated with continuous cropping. In the present study, fungal diversity was higher in continuously cropped soil than that in 0_Y soil. Thus, we conclude that fungal richness and evenness may increase with the duration of continuous cropping. The top 10 fungal genera found in rhizosphere soil in this study differed from those reported in a previous study of fungal superiority in rhizosphere soil (Nallanchakravarthula et al. 2014). This difference might be due to the use of continuous cropping or the physiochemical characteristics of the soil itself. In the present study, we selected the >1%
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roots. The genus Fusarium contains many pathogenic species; thus, an increase in Fusarium abundance is likely to lead to plant disease. Guehomyces is often used in the degradation of industrial waste products; it can degrade lignin-containing wastes through its ligninase and Mnperoxidase activities (Sláviková et al. 2002). Humicola produces cellulose acetate deacetylase; the biodegradative activity of this enzyme in disposal environments (compost, wastewater, and soil) decreases as the degree of substitution increases (Olaru et al. 2004; Puls et al. 2004, 2011), resulting in an increase in the levels of lignin, cellulose and hemicellulose in the soil. Increased levels of these compounds generally lead to an increase in the number of nematodes that feed on crop plants. In contrast, the relative abundance of Acremonium and Artrobotrys declined significantly (P<0.05) after continuous cropping (Fig. 4-D and E). Arthrobotrys has been shown to kill 85% of nematodes within 6 h of contact (Song et al. 2017); in the present study, the abundance of Arthrobotrys decreased significantly after four years of continuous cropping (Fig. 4). Hence, many plant nematodes, including Meloidogyne, Tylenchus and Pratylenchus, might survive because the pathogen density
most abundant species and used these to analyse the fungal community patterns that are presumably linked to the adverse effects of continuous cropping at the genus level (Fig. 2-A). The results showed that among 32 genera, nine genera (Guehomyces, Arthrobotrys, Gibellulopsis, Myriococcum, Humicola, Mortierella, Fusarium, Acremonium and Aspergillus) displayed significant differences (P<0.05) after continuous cropping (Figs. 2-A and 4). The functions of these nine fungi mainly include the production of soilborne diseases, defence and decomposition. Most soilborne diseases are caused by soil fungi such as Fusarium oxysporum (Gullino et al. 2002), Gibellulopsis (Zhou et al. 2017), Pyrenochaeta lycopersici (Campbell et al. 1982) and Verticillium spp. (Harris 1990). Increases in the number of soil-borne disease pathogens can aggravate the effects of continuous cropping. In particular, the relative abundances of Fusarium, Guehomyces, and Humicola significantly increased (P<0.05) after continuous cropping (Fig. 4-A, B and H). Fusarium proliferatum can infect garlic roots and produce mycotoxins during crop growth (Gálvez et al. 2017). Fusarium graminearum and Gibberella zeae cause stalk rot in maize and infect plants by directly penetrating seedling
–0.084
–0.016
–0.079
–0.313
–0.424
–0.304
Penicillium
–0.125
–0.276
–0.252
–0.022
–0.273
–0.466
Monographella
–0.087
–0.035
–0.123
–0.075
–0.354
–0.46
Pseudallescheria
–0.087
–0.069
–0.126
–0.003
–0.318
–0.416
Chaetomium
–0.659
–0.78
–0.757
–0.024
–0.324
–0.327
Cryptococcus
–0.679
–0.653
–0.691
–0.061
–0.17
–0.239
Fusarium
–0.612
–0.692
–0.691
–0.092
–0.203
–0.192
Funneliformis
–0.581
–0.562
–0.542
–0.096
–0.049
–0.101
Olveonia
–0.523
–0.481
–0.517
–0.097
–0.198
–0.294
Gibberella
–0.525
–0.616
–0.596
0.153
–0.198
–0.361
Humicola
–0.296
–0.418
–0.391
–0.223
–0.528
–0.683
Mortierella
–0.521
–0.629
–0.64
–0.005
–0.396
–0.473
Guehomyces
–0.338
–0.493
–0.438
–0.034
–0.428
–0.570
Gibellulopsis
–0.362
–0.388
–0.444
–0.006
–0.348
–0.369
Cephaliophora
–0.153
0.034
0.023
0.071
0.292
0.422
Olpidiaster
0.425
0.595
0.474
0.047
0.218
0.081
Arthrobotrys
0.751
0.815
0.799
–0.096
–0.055
–0.014
Microascus
0.242
0.506
0.384
–0.579
–0.301
–0.168
Myriococcum
0.186
0.212
0.194
–0.165
–0.327
–0.527
Aspergillus
0.344
0.468
0.390
–0.130
–0.240
–0.453
Acremonium
0.360
0.402
0.309
–0.081
–0.180
–0.370
Thermomyces
AK
pH
NH4+-N
AP
TN
SOM
0.8 0.6 0.4 0.2 0.0 –0.2 –0.4 –0.6
Fig. 5 Spearman’s correlation heatmap based on population abundance and environment variables at the genus level for genera with abundance>1%. The phylogenetic tree was calculated using the neighbour-joining method, and the relationship among the environmental variables was determined using the Bray distance and the complete clustering method. The heatmap plot depicts the correlation between environmental variables (AK, rapidly available potassium; NH4+-N, ammonium nitrogen; AP, rapidly available phosphorus; TN, total nitrogen; SOM, soil organic matter) and fungal genera with abundance>1%. Red indicates positive correlations; green indicates negative correlations.
LI Wei-hua et al. Journal of Integrative Agriculture 2019, 18(3): 677–687
is low and food availability is increased. In addition, fungal endophyte Acremonium species are important in plant disease control (Redman et al. 1999). In particular, the content of Fusarium, Guehomyces, Humicola, Acremonium and Artrobotrys changed significantly after the fourth year of continuous cropping. Previous research has shown that soil fertility and the presence of microorganisms are closely related to crop yields (Pešaković et al. 2013). These changes in fungal populations might lead to decreased soil health and reduced crop yields.
4.3. Correlations between environmental data and fungal communities Previous studies have reported an association between soil physicochemical properties and the metabolism of microorganisms (Wolters 2000; Tang et al. 2013; Xie et al. 2017). Similarly, this study showed that AK, pH and NH4+-N significantly influence soil fungal diversity according to Spearman’s correlation analysis (Fig. 5). In addition, Fusarium, Guehomyces and Arthrobotrys were associated with soil physicochemical properties, and the fungi of these genera differed significantly in abundance (abundance >1%). Hence, Fusarium, Guehomyces and Arthrobotrys might be the key fungal species associated with continuous cropping.
5. Conclusion This study showed that the soil environment changes significantly after continuous cropping of strawberry. With the changing trend in soil physicochemical properties, the soil nutrient content began to decline after the fourth year of continuous cropping. Continuous cropping reduced the AK, pH and NH4+-N content of the soil and altered the fungal community in the soil environment. The results suggested that Fusarium, Guehomyces and Arthrobotrys might be the key fungi associated with continuous cropping. Fungal diversity and evenness increased significantly in the twelfth year of continuous cropping. Moreover, the relative abundance of plant pathogenic fungi of the genus Fusarium gradually increased as the duration of continuous cropping increased. Determining the fungal mechanisms that affect plant growth is among the future challenges of agricultural ecological research. However, exploring the complexity of the interactions between plant roots and fungi within the soil environment will be particularly difficult.
Acknowledgements The present study was funded by the National Science and Technology Support Program of China (2014BAD16B07).
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