Funneliformis mosseae alters soil fungal community dynamics and composition during litter decomposition

Fungal Ecology 43 (2020) 100864

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Funneliformis mosseae alters soil fungal community dynamics and composition during litter decomposition Heng Gui a, b, c, d, Witoon Purahong e, Tesfaye Wubet e, f, Derek Per
soh g, Lingling Shi a, b, Sehroon Khan a, Huili Li a, Lei Ye a, b, Kevin D. Hyde c, d, Jianchu Xu a, b, **, Peter E. Mortimer a, * a

Key laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Science, Kunming, 650201, China Centre for Moutain Futures (CMF), Kunming Institute of Botany, Chinese Academy of Science, Kunming 650201, Yunnan, China Centre of Excellence in Fungal Research, Mae Fah Luang University, Chiang Rai, 57100, Thailand d School of Science, Mae Fah Luang University, Chiang Rai, 57100, Thailand e Department of Soil Ecology, UFZeHelmholtz Centre for Environmental Research, Halle (Saale), D 06120, Germany f German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, D 04103, Germany g €t Bochum, Universita €tsstraße 150, 44801, Bochum, Germany Geobotanik, Ruhr-Universita b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 27 March 2019 Received in revised form 19 August 2019 Accepted 22 August 2019 Available online 9 November 2019

Recent studies have indicated that arbuscular mycorrhizal fungi (AMF) are able to influence litter decomposition by interacting with the soil fungal community. However, it remains unclear exactly which constituent groups of the soil fungal community respond to AMF during litter decomposition, and in what ways. To better understand this relationship, we investigated the effect of AMF on soil fungal communities in a greenhouse experiment. Our study found that the composition and richness of the fungal community, at higher taxonomical levels (e.g. phyla, order), remained stable across treatments. However, the relative abundance of some key genera including Mycena, Glomerella, Pholiotina, and Sistotrema were significantly affected by AMF inoculation. Soil fungal community structure was also altered by AMF inoculation during the later stages of litter decomposition. Our study provides new insights into understanding the interaction between AMF and soil fungal communities and reinforces the importance of AMF in soil nutrient cycling. © 2019 Elsevier Ltd and British Mycological Society. All rights reserved.

Corresponding Editor: Bala Chaudhary Keywords: Culture independent technique Illumina sequencing Litter decomposition Soil fungi Soil microbial communities

1. Introduction Litter decomposition is a crucial component of nutrient cycling (Lavelle et al., 1993). Both biochemical and physical processes are essential to litter decomposition (Song et al., 2010). The mineralization and humification of lignin, cellulose, and other organic compounds by a succession of microorganisms is particularly important (Garcia-Palacios et al., 2013). Their key role in litter decomposition was highlighted by Berg et al. (2003), who reported that microorganisms were responsible for around 95% of the litter decomposition in coniferous forests, while the remaining 5% was due to the activities of animals. * Corresponding author. ** Corresponding author. Key laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Science, Kunming, 650201, China. E-mail addresses: [email protected] (H. Gui), [email protected] (J. Xu), [email protected] (P.E. Mortimer). https://doi.org/10.1016/j.funeco.2019.100864 1754-5048/© 2019 Elsevier Ltd and British Mycological Society. All rights reserved.

Soil fungi, especially saprotrophic fungi, are believed to be primary decomposers due to their production of various extracellular enzymes (de Boer et al., 2005), which also play a central role in carbon, nitrogen, and phosphorus cycling (Whitman et al., 1998). Soil fungi take part in all phases of litter decomposition, but different fungal phyla are dominant at different times. Members of the phylum Ascomycota play a crucial role during the early stages of decomposition, while Basidiomycota are more active during the
later stages (Osono, 2007; Snajdr et al., 2011). Studies using nextegeneration sequencing have shown that various fungal taxa mediate the highly complex process of litter decomposition  and Baldrian, 2013). (Vo
rí
skova Arbuscular mycorrhizal fungi (AMF) are an abundant and ubiquitous group of soil fungi able to form symbiotic associations with major terrestrial plants. Unlike other soil saprotrophic fungal groups, AMF have no known saprotrophic abilities (Read and PerezeMoreno, 2003). AMF play a central role in plant nutrient acquisition during litter decomposition, but this effect is indirect

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and relies on the ability of saprotrophic soil microorganisms to decay complex organic materials in the soil (Hodge, 2001; Leigh et al., 2011). AMF interact with other soil microorganisms through exudates released from external mycelia. These exudates are mainly low molecular weight compounds such as sugars, amino acids, and organic acids (Toljander et al., 2007). In recent years, this interaction between AMF and other members of the soil fungal community during litter decomposition has gained more attention due to the contribution of AMF to C sequestration and N dynamics (Cheng and Gershenson, 2007). However, the mechanism of this interaction remains controversial. While Toljander et al. (2007) and Albertsen et al. (2006) showed that the presence of AMF led to increased soil bacterial and fungal biomass, some studies have found that AMF had an inhibitory effect on soil microbial communities (Gui et al., 2017). Welc et al. (2010) found that the presence of Rhizophagus intraradices and Funneliformis mosseae reduced the amount of Gram-negative bacteria and soil fungi in root-free soil after 6 weeks. Similarly, Mechri et al. (2014) found that R. intraradices reduced the amount of both Gram positive and negative bacteria compared to uninoculated treatments. In contrast, some studies have reported that AM fungal inoculation has no significant effect on the soil microbial community during litter decomposition (Hodge, 2001; Herman et al., 2012). The interaction between AMF and saprotrophic fungi is especially important in subtropical forest soils, where AMF are widely distributed (Alexander et al., 2005) and high primary productivity drives photosynthetically fixed C from the plants to the soil via AMF networks (Pan et al., 2011). Our previous study (Gui et al., 2017) made use of phospholipid fatty acids (PLFA) analysis to show that AMF inoculation suppressed other soil fungi during litter decomposition, and postponed increases in fungal biomass during the litter decomposition process. Although PLFA is an effective and widely used method for monitoring the influence of AMF on the soil microbial communities (Hodge, 2001; Hobbie and Horton, 2007; Herman et al., 2012; Nottingham et al., 2013), the technical limitations of this technique mean it is unsuited for detailed examination of taxonomic change in soil fungi (Frostegard et al., 2011). Given that different types of soil saprotrophic fungi (Ascomycota and Basidiomycota) may act as the main decomposers under different conditions (e.g. time, treatment, environmental change) (Bastian et al., 2009; Sherman et al., 2014), it is necessary to closely examine the phylogenetic and functional changes in soil fungal communities induced by AMF inoculation. The application of nextegeneration sequencing tools to microbial ecology offers the opportunity to comprehensively examine the effects of AM fungal inoculation on the composition of the saprotrophic fungal community during litter decomposition (Verbruggen et al., 2010; Dumbrell et al., 2011; Lentendu et al., 2011; Kuramae et al., 2013). The aims of this study were to better understand the effects of AMF on (i) soil fungal community composition and dynamics, and (ii) to assess how this relationship changes through time. Based on our previous study (Gui et al., 2017) where we reported that AMF mycelia suppress the development of soil saprotrophic fungal communities, we hypothesized that (i) fungal genera and functional groups related to C and N dynamics in the soil are influenced by AMF inoculation, and (ii) the effects of AMF inoculation on fungal genera and functional groups follow a temporal change pattern. 2. Materials and methods 2.1. Materials used in the experiment The microcosm experiments described in this paper were built from several major experimental materials including AMF

inoculum, field soil, host plants, and litter bags. Detailed information about these materials and their properties is given in the Supplementary Data of our previous study (Gui et al., 2017). The AMF inoculum was a mixture of the F. mosseae spores and the sterile rock flour materials. The soil applied in this experiment was sampled from a subtropical forest located in southwestern China. The litter bags buried in the soil contained dried leaves of Calophyllum polyanthum, an indigenous species that is abundant in the forest where soil was collected. In this experiment, we selected Trifolium repens, a major AMF plant, as the host plant. 2.2. Experimental set up Our experiments were conducted in an acrylic microcosm unit consisting of two compartments modified from those described in Herman et al. (2012). The design is described in detail in Gui et al. (2017) and is given in Fig. S1 in Supplementary Data. The first compartment (Host), used to pot the host plant, was filled with sterilized vermiculite and fine gravel (ca. 0.3 cm diameter), which was evenly mixed in a 1:1 ratio. For the AM fungal inoculation treatment, 20 g of AMF inoculum (F. mosseae) was added to the potting medium. Forest soil was placed in the second compartment. A litter bag (5 cm
5 cm) was placed in the soil at a depth of 5 cm in both compartments. The litter bag was made of 200 mm nylon mesh. The litter is made from dried C. polyanthum leaves. The process of making dried leaves is given in Gui et al. (2017). The microcosms were divided into two treatments: with AMF inoculation (AM) and without AMF (NM). Four replicates were set up for each treatment and timepoint, and samples were harvested at four times at monthly intervals. A total of 32 microcosms were set up for the experiment. All microcosms were set up in a randomized design in a greenhouse, where the daily temperature ranged from 20 to 25  C. All compartments and plants received natural light only and no rainwater. 2.3. Plant growth and mycorrhizal colonization 0.2 g of T. repens seeds were sown in the Host compartment of the microcosm. 2 weeks after the sowing, the Host compartment received 10 ml of distilled water twice a week and 10 ml of modified Long Ashton nutrient solution according to Hewitt and Bureaux (1966) once a week. At the same time, the Litter compartments received 10 ml of distilled water once per week to maintain moisture levels. After 2 weeks the N and P concentrations in the Long Ashton solution were modified to 1/10th of the original concentration (34 mg l1 NaNO3 þ 21.4 mg l1 NH4Cl, 29.2 mg l1 NaH2PO4∙2H2O þ 4.7 mg l1 Na2HPO4∙12H2O, pH ¼ 7.0) according to Leigh et al. (2009). The colonization of T. repens roots by AMF was determined using dyeing methods described by Vierheilig et al. (1998). The detailed protocol is given in Gui et al. (2017). The percentage of colonization was calculated by a modified line intersection method (McGonigle et al., 1990). Detailed colonization rate data for each sampling time is described in Gui et al. (2017) and given in Fig. S2 in Supplementary Data. 2.4. Soil sampling and DNA extraction The forest soil used for the experiment (T0) was sampled and preserved at 20  C for later DNA analysis. The first sampling from the microcosm experiment was conducted 90 d (T90) after sowing. Subsequent sampling times were at 120 d (T120), 150 d (T150) and 180 days (T180) after sowing. At each sampling, 5 g of the soil around the litter bag was collected for further molecular analysis. Total soil genomic DNA was extracted from 2 g of fresh soil using the OMEGA

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Soil DNA kit (Omega bio-tek, Norcross, Georgia) according to the manufacturer's protocol, and DNA extracts were stored at 80  C until PCR amplification. 2.5. PCR amplification and sequencing All DNA samples were quantitated with the NanoDrop NDe1000 spectrophotometer (NanoDrop technologies). According to the concentration, DNA was diluted to 1 ng ml1 using sterile water for PCR amplification of the Internal Transcribed Spacer 2 (ITS2) region of the ribosomal RNA gene. The fungal ITS region has been widely accepted as the universal marker for fungi (Schoch et al., 2012), which enabled us to target the ITS2 fragment using the pairedeend Illumina MiSeq approach using the forward primer fITS7 (Ihrmark et al., 2012) and reverse primer ITS4 (White et al., 1990). The PCR reaction was performed in a 50 ml reaction mixture that contained approximately 10 ng of DNA, ExTaq buffer, 0.2 mM of dNTPs, 0.2 mM of each primer, and 2 units of ExTaq DNA polymerase. Cycling consisted of an initial denaturation at 94  C for 30 s, followed by 25 cycles of denaturation at 94  C for 30 s, annealing at 54  C for 1 min and extension at 72  C for 2 min, and a final extension at 72  C for 8 min. All PCR reactions were carried out with Phusion® HigheFidelity PCR Master Mix (New England Biolabs Inc. Ipswich, MA, USA). The PCR products were mixed with the same volume of 1
loading buffer (contained SYB green) and electrophoresis with 2% agarose gel was performed on the PCR products for quality detection. Only samples with a bright main strip between 400 and 450 bp were chosen for further experiments. The qualified PCR products were mixed in equidensity ratios. Then, mixture PCR products were purified with Qiagen Gel Extraction Kit (Qiagen, Germany) following the manufacture's protocol. Sequencing libraries were generated using TruSeq® DNA PCReFree Sample Preparation Kit (Illumina, San Diego, CA, USA) following manufacturer's recommendations, and index codes were added. The library quality was assessed on the Qubit® 2.0 Fluorometer (Thermo Scientific) and Agilent Bioanalyzer 2100 system. The library was sequenced on an Illumina HiSeq2500 platform and 250 bp paired-end reads were generated. 2.6. Bioinformatic analysis Paired-end reads were assigned to samples based on their unique barcodes or indices truncated by removal of the barcode and primer sequence. Pairedeend reads were merged using FLASH (V1.2.7, http://ccb.jhu.edu/software/FLASH/) (Mago
c and Salzberg, 2011), which was designed to merge pairedeend reads when the reads overlap by 10 bases with the read generated from the opposite end of the same DNA fragment, and the splicing sequences of the fragment were called raw tags. Quality filtering on the raw tags was performed under specific filtering conditions to obtain high-quality clean tags (Bokulich et al., 2013) according to the QIIME (V1.7.0, http://qiime.org/index.html) quality controlled process (Caporaso et al., 2010). The tags were compared with the reference database (UNITE Database, https://unite.ut.ee/) using UCHIME algorithm (UCHIME Algorithm, http://www.drive5.com/ usearch/manual/uchime_algo.html) to detect chimera sequences (Edgar et al., 2011). Chimera sequences were removed (Haas et al., 2011) and the Effective Tags were finally obtained. Sequence analysis was performed by UPARSE software (UARSE v7.0.1001,http://drive5.com/uparse/) (Edgar, 2013). Sequences with 97% similarity were assigned to the same operational taxonomic units (OTUs). A representative sequence for each OTU was screened for further annotation. For each representative sequence, the UNITE

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Database (https://unite.ut.ee/) (Koljalg et al., 2013) was used to annotate taxonomic information based on Blast algorithm, which was calculated by QIIME software (Version 1.7.0) (http://qiime.org/ scripts/assign_taxonomy.html). To study the phylogenetic relationships between different OTUs, and the difference of the dominant species in different samples (groups), multiple sequence alignments were conducted using the MUSCLE software (Version 3.8.31, http://www.drive5.com/muscle/) (Edgar, 2004). All the OTUs abundance information was normalized using a standard number of sequences corresponding to the sample with the least sequences (49017). Subsequent analyses of alpha diversity and beta diversity were all performed basing on these normalized data. The fungal ITS rRNA gene sequences, derived from the Illumina sequencing data were deposited in the Sequence Read Archive (SRA) of National Center for Biotechnology Information (NCBI) under the BioProject number PRJNA391050. 2.7. Diversity and statistical analyses To test the effects of AMF inoculation and time on fungal OTU richness and diversity, the Chao1 richness estimator and the Shannon diversity index were calculated with QIIME (Version 1.7.0) and displayed with R software (Version 2.15.3). One-way analysis of variance (ANOVA) with a general linear model (GLM) procedure was performed by SPSS 18.0 to assess the differences of the composition of the soil fungal community between sampling times and treatments (AM and NM). The results were shown as mean values with standard error. The significant differences were determined by using Duncan's multiple range tests at P < 0.05. Two-way permutational multivariate analysis of variance (PERMANOVA) based on Bray-Curtis (abundance data) and Jaccard (presence/absence data) distances were applied to investigate the effect of incubation time and AMF inoculation treatment on fungal community structure (Hammer et al., 2001) using the software PAST. Principal component analysis (PCA) was performed to obtain principal coordinates and visualize the complex, multidimensional data related to the detected OTUs. A distance matrix of weighted or unweighted UniFrac among different soil samples was transformed to a new set of orthogonal axes, according to which the maximum variation factor was demonstrated by the first principal coordinate, and the second maximum variation by the second principal coordinate, and so on. PCA was calculated using the WGCNA package, stat packages and ggplot2 package in R software (Version 2.15.3). 3. Results 3.1. Description of fungal community composition A total of 49,017 quality filtered fungal sequences per sample (average length of 243 bp) survived after barcode and primer trimming and chimera removal, and were clustered into 4706 fungal OTUs at a 97% similarity level of taxonomic resolution. Ascomycota and Basidiomycota were the most frequently detected phyla, and together accounted for more than 80% of the average relative abundance, followed by Glomeromycota, Rozellomycota, Chytridiomycota, Zygomycota, and other unspecified groups. The relative abundance of these fungal phyla varied with sampling time and among treatments (Fig. 1A). Ascomycota accounted for 48.2% of the average relative abundance across all samples and reached its peak abundance (67.5%) at T90 in the treatment without AM fungal inoculation. In the treatment with AMF inoculation, Ascomycota also reached its highest level of abundance at T90, but the abundance was lower (49.5%). When comparing abundance levels between different treatments (AM and NM), AM treatment decreased the relative abundance of

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Fig. 1. The relative abundance of the dominant fungal phyla (A) and orders (B) in soil samples from the arbuscular mycorrhiza inoculated treatment (AM) and non mycorrhizal inoculation control (NM) and harvesting times (T0, T90, T120, T150 and T180, indicated by O, 1, 2, 3 and 4 respectively). Relative abundance (>1%) is based on the proportional frequencies of those DNA sequences that could be classified at the phylum or order levels. Phylogenetic groups that account for less than 1% of all classified sequences are divided into the artificial group “others”.

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Fig. 2. Heatmap and accompanying cluster analysis (x-axis) of the relative abundance of dominant fungal genera or phylotypes in all the soil samples from the arbuscular mycorrhiza inoculated treatment (AM) and non mycorrhizal inoculation control (NM) and harvesting times (T0, T90, T120, T150 and T180, indicated by O, 1, 2, 3 and 4 respectively). Mean relative abundance is shown for each sample. For each genus, a significant difference either between different sampling times or treatments is denoted by an asterisk “*” (P < 0.05). Treatments with a letter in common are not different at P < 0.05 according to the Duncan's multiple range test. Differences were tested among treatment combinations (harvesting times (O is not included) and arbuscular mycorrhizal inoculation or not) for each genus (per row). The relative abundance for each genus in each soil sample is colored in the shades of light blue (low relative abundance) to red (high relative abundance).

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Table 1 Permutational multivariate analysis of variance (PERMANOVA) on the effect of the AM treatment and harvesting time, based on BrayeCurtis (abundance data). Factors

Sum of squares

df

Mean square

F value

P value

AMF Harvesting time

0.3459 1.324

1 3

0.3459 0.4413

1.7489 2.2311

0.014 0.001

Note: P value was based on 999 permutations. Bold font indicates significant differences (P < 0.05). Abbreviation: AMF (Arbuscular mycorrhizal fungi).

Penicillium, Xylaria, Trechispora genera and for one unclassified genus from Orbiliaceae. During the later stages of decomposition (T150eT180), AMF inoculation increased the relative abundance of Clitopilus, and one genus from Atheliales, but decreased the relative abundance of Sistotrema, Gliocladiopsis, Talaromyces, Trechispora, and two unclassified genera from Lecanoromycetes and Rozellomycota. 3.3. Impact of AMF inoculation and sampling time on fungal community composition Each sampling time per treatment was characterized by a specific fungal community (PERMANOVA, PseudoFAMF ¼ 1.75, P ¼ 0.014 and PseudoFsampling time ¼ 2.23, P ¼ 0.001 (relative abundance data) (Table 1). The abundance of all detected OTUs was analyzed by PCA, which showed that the first two canonical axes explained 65.2% and 11.3% of the total variability. The PCA ordination indicated that fungal communities from the AM fungal inoculation treatment were different from the control treatment at all sampling times except for T90. Composition of the fungal community during the early stages of litter decomposition differed from that of later stages both with and without AMF inoculation (Fig. 3). 3.4. Effects of AMF inoculation on fungal diversity and richness

Fig. 3. Principal component analyses (PCA) of relative abundance of all the fungal OTUs detected in the soil samples from the arbuscular mycorrhiza inoculated treatment (AM) and non mycorrhizal inoculation control (NM) and harvesting times (T0, T90, T120, T150 and T180, indicated by O, 1, 2, 3 and 4 respectively). The data is shown at mean value for each axis (±SE, n ¼ 4).

Ascomycota for all sampling times except for T120, where nearly the same value was detected between treatments. Peak abundance for Basidiomycota (40.9%) was detected at T180 for the AM treatment. At each sampling, AM treatment increased the relative abundance of Basidiomycota at T150 and T180, while decreasing the abundance at T120, when compared with non-mycorrhizal inoculation. Glomeromycota was the 3rd most abundant phylum, and its relative abundance varied widely across different samples, from less than 1% at T90 with AMF inoculation to 28.8% at T120. The AM treatment increased the relative abundance of Glomeromycota compared with the control treatment between T90 and T150. Changes in the relative abundance of the ten most abundant fungal orders were not consistent across sampling times and different treatments (AM and NM) (Fig. 1B). 3.2. Effects of AMF inoculation on fungal community dynamics A total of 855 fungal genera were identified as the closest hits of individual OTUs. The 35 most abundant genera were selected for closer examination, 27 of which demonstrated significant changes (P < 0.05) in abundance either over time or due to AMF inoculation (Fig. 2). During the early stages of litter decomposition (T90eT120), AM fungal inoculation significantly increased the relative abundance of Mycena, Glomerella, Pholiotina, and Sistotrema, and three unclassified genera from Glomeromycota, Onygenales, Chitrydiomycota. Furthermore, relative abundance decreased for

Although we obtained a high number of fungal sequence reads per sample (49,017), the numbers of OTUs also increased with the number of sequences without reaching a plateau (Fig. S3 in Supplementary Data). Fig. 4 The Shannon diversity (Fig. 4A) and Simpson's richness (Fig. 4B) indices based on observed detected OTUs decreased over time, but this trend reversed in the last month of the experiment. The only significant decrease in Shannon index was detected at T120 with AMF inoculation. However, the Chao1 index showed no significant changes over time or between treatments (Fig. 4C). We also assessed OTU richness in different fungal orders and families between different treatments and over different sampling times. The results showed that AM did not affect OTU richness significantly in single orders and families. The most OTU-rich orders under the NM treatment were Hypocreales (84 OTUs) followed by Eurotiales (76 OTUs), Agaricales (67 OTUs), Helotiales (65 OTUs), and Chaetothyriales (48 OTUs). A similar pattern was found for the most OTU-rich orders under the AM treatment: Hypocreales (75 OTUs) followed by Eurotiales (70 OTUs), Helotiales (61 OTUs), Agaricales (57 OTUs), and Chaetothyriales (57 OTUs). Changes in OTU richness of the 20 most abundant orders over time and under different treatments are shown in Fig. 5. At the family level, the same analysis and significance tests were applied, and no significant effects were detected. We found that the fungal families with the highest number of OTUs under both the control and AMF inoculation treatments was Trichocomaceae (AM ¼ 62 OTUs, NM ¼ 68 OTUs), followed by Herpotrichiellaceae (AM ¼ 39 OTUs, NM ¼ 39 OTUs), Archaeorhizomycetaceae (AM ¼ 36 OTUs, NM ¼ 43 OTUs) and Sclerodermataceae (AM ¼ 22 OTUs, NM ¼ 22 OTUs). Detailed changes in OTU richness of the 25 most abundant families over time and under different treatments are shown in Fig. 6. 4. Discussion Nextegeneration sequencing techniques (NGS) have enabled researchers to extend analysis of fungal diversity in detailed and comprehensive ways. However, to our knowledge, this is the first study applying NGS to analyze the effects of AM fungal inoculation on soil fungal community composition and shifts in these communities over time during litter decomposition.

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Fig. 4. The (A) Shannon, (B) Simpson richness and (C) Chao1 indices of soil fungal communities based on all the detected OTUs under different treatments (AM (the treatment inoculated with arbuscular mycorrhizal fungi) and NM (Non mycorrhizal inoculation control)) with time. Data are presented as means ± SE (n ¼ 4). Different letters indicate significant differences (P < 0.05).

4.1. Effect of AMF on fungal community composition at different taxonomic resolutions Our previous study (Gui et al., 2017) using the same experimental design revealed that AMF inoculation had a significant effect on soil fungal biomass by suppressing the growth of other soil fungi after T120. In addition, Welc et al. (2010) also showed that the amount of fungal biomarker was reduced by 36% with F. mosseae inoculation compared with an uninoculated control. However, the interaction between AMF and the soil fungal communities during litter decomposition can be inhibitory, stimulatory, or neutral, and the effect varies with litter quality (Gryndler et al., 2002), soil substrate (MansfeldeGiese et al., 2002), and/or host plant (Marschner and Timonen, 2005). For instance, Hodge et al. (2001)

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and Herman et al. (2012) found that the presence of AMF did not affect fungal biomass based on PLFA profiles in 42 d and 70 d pot experiments, during the decomposition of Plantago lanceolata root litter. However, due to the low resolution of PLFA techniques when quantifying and characterizing complex fungal communities, it remains unclear whether, or to what extent, AMF affected fungal diversity and community composition in these two studies as well as our previous study (Gui et al., 2017). Our study revealed detailed insights into the interaction between soil fungal communities and AMF during litter decomposition at different taxonomic levels. Previous studies using litter bags  and Baldrian, 2013), or conducted (Kuramae et al., 2013; Vo
rí
skova in natural forests (Per
soh et al., 2013; Treseder et al., 2014), have demonstrated that soil fungal communities undergo successional changes during litter decomposition. In our study, at T120 and T180, the AM treatment led to a decline in the relative abundance of both Ascomycota and Basidiomycota, widely accepted as the main saprotrophic soil fungal decomposers (Vandenkoornhuyse et al., 2002). Furthermore, when considering the effect of AMF inoculation on the soil fungal communities, the suppression caused by AMF inoculation observed in our study was consistent with our previous findings, that the presence of F. mosseae suppressed the development of fungal biomass (Gui et al., 2017). Previous studies have shown that the interaction between AMF and other soil fungi could be positive (Albertsen et al., 2006; Toljander et al., 2007), neutral (Hodge et al., 2001; Herman et al., 2012) or negative (Nuccio et al., 2012). Due to the taxonomic and functional resolution of our approach, we were able to show that not all taxonomic groups of the fungal community members were suppressed by inoculation with AMF: although the total species decreased under AM treatment, the relative abundance of some fungal groups was enhanced. At the phylum level, this suppression mainly affected members of the phylum Ascomycota, which was the most abundant fungal group within our soil samples, and agrees with the work of Ma et al. (2013). However, due to the high lignin content of forest soils, fungi from the phylum Basidiomycota are thought to be the key decomposers in this environment (Blackwood et al., 2007). Our observation that in the early stage of litter decomposition, the relative abundance of Basidiomycota was enhanced by AMF could explain the acceleration of litter decomposition caused by the AMF inoculation revealed by our previous study (Gui et al., 2017). Like other climate factors, humidity is considered to be a major feature regulating litter decomposition in various terrestrial ecosystems (Krishna and Mohan, 2017) as well as the fungal decomposer community in the soil (Logan et al., 2018). Some incubation research has shown that increasing the humidity of dry soil results in increasing decomposition rates (Fierer and Schimel, 2003), while field experiments have demonstrated similar findings (Yuste et al., 2003). In our study, soil moisture in the microcosms was kept stable by watering regularly to minimize the effect of soil humidity on litter decomposition and the fungal community. We also found a pattern in the change of soil fungal community composition at the order level as a result of AMF. AMF inhibited the growth of Hypocreales and Tremellales, even though these functional groups are believed to be associated with litter decomposition (Kuramae et al., 2013; Ma et al., 2013,Kuramae et al., 2013). Combined with the enhanced rates of litter decomposition described in Gui et al. (2017), these findings indicate that AMF may occupy the ecological niche ordinarily filled by other decomposers, and may play a direct role in litter decomposition. This result is also supported by the work of Hodge et al. (2001), but is otherwise seldom reported. In the early stage of litter decomposition, AMF may interact with several other fungal genera, which increased in abundance under AM treatment. Among the genera that increased

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Fig. 5. The OTU richness (the number of observed OTUs) of the 20 most abundant soil fungal orders for AM (Treatment inoculated with arbuscular mycorrhizal fungi) and NM (Non mycorrhizal inoculation control) and harvesting times (T0, T90, T120, T150 and T180, indicated by O, 1, 2, 3 and 4 respectively). Different letters indicate significant differences (P < 0.05).

in abundance under AM treatment was Mycena, a well known

 et al., 2011). lignin degrader (Miyamoto et al., 2000; Zif c akova Mycena is also known to increase the rate of litter decomposition, which again contributes towards our understanding of the increased rates of decomposition observed in the early stages of litter decomposition in other studies (Hanackova et al., 2015; Gui et al., 2017). The interaction between AMF and members of the soil fungal community has been demonstrated in numerous studies (Driver et al., 2005; Hooker et al., 2007; Toljander et al., 2007; Welc et al., 2010). It is believed that AMF affects other soil fungi through the release of low molecular weight exudates (e.g. glomalin, amino acids, organic acids) via external mycelium (Marschner and Timonen, 2005). Some sugar exudates are believed to be crucial for the growth of microbial communities living in the AMF hyphosphere (Hooker et al., 2007). This could help explain the increased abundance of several fungal groups observed in our current study. However, in addition to this observed increase in

abundance of certain groups, we also observed a decline in other groups because of the AM treatment. A possible explanation is that the presence of AMF can occupy soil fungal niches (Veresoglou et al., 2011) or compete for carbohydrate resources with other fungi (Baggi, 2000), which could lead to suppression observed in our study.

4.2. Fungal community dynamics Our study identified clear shifts in the composition of soil fungal communities during litter decomposition, both with and without AMF inoculation. This pattern of fungal succession during litter decomposition is consistent with several previous studies (Bastian et al., 2009; Hanackova et al., 2015). Similar patterns of fungal community succession were reported by Hanackova et al. (2015), who investigated the decomposition of Picea abies needle litter. In addition, a 168 d study of wheat straw decomposition revealed that there were significant differences in the structure of fungal

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Fig. 6. The OTU richness (the number of observed OTUs) of the 20 most abundant soil fungal families for AM (the treatment inoculated with arbuscular mycorrhizal fungi) and NM (Non mycorrhizal inoculation control and harvesting times (T0, T90, T120, T150 and T180, indicated by O, 1, 2, 3 and 4 respectively). Different letters indicate significant differences (P < 0.05).

communities between the early stage (14e28 d) and late stage (56e128 d) of decomposition (Bastian et al., 2009). This is consistent with our findings, which showed significant change occurring at T120. However, when testing the alpha diversity indices of the soil fungal communities, richness and diversity remained stable for the duration of our experiment. This finding agreed with previous reports (Ma et al., 2013; Hanackova et al., 2015) that there were no observed changes in the diversity of soil fungal communities during

litter decomposition, despite observed compositional changes. One possible explanation is taxon reordering while diversity remains the same and fungal composition changes (Oliver et al., 2015), or alternatively, there may be undocumented changes in fungal biomass or activities that would not have affected the diversity. PCA analysis showed there was a significant difference in soil fungal community composition between the AM and NM treatments at T120. This difference is in accordance with earlier studies

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(Welc et al., 2010; Mechri et al., 2014), which reported several strains of AMF having clearly differing effects on soil fungal communities, as compared to their noneinoculated controls. It is believed that these differences are due to exudates released by the external mycelium of the AMF (Welc et al., 2010). Additionally, we demonstrated temporal patterns during litter decomposition. Combining these results with our analysis of rarefaction curves and alpha diversity, we inferred that the effect of AMF on other soil fungi could be generally regarded as “suppression” at the community level, despite not all functional groups being inhibited. This suppression likely occurred in the early stages of litter decomposition. Acknowledgements This research was funded by the CPSF-CAS Joint Foundation for Excellent Postdoctoral Fellows (Grant No.: 2017LH029), the China Postdoctoral Science Foundation (Grant No.:2018M633435) and the 2018 Yunnan Province Postdoctoral Science Research Foundation. Heng Gui would like to thank the support from the Human Resources and Social Security Department of Yunnan Province, German Academic Exchange Service (DAAD) under the program: Research Stays for University Academics and Scientists, 2018 (Ref. No.: 91691203) and the China Scholarship Council under the State Scholarship Fund (Ref. No.: 201804910259). We also would like to thank the help from Biological technology open platform, Kunming Institute of Botany, Chinese Academy of Sciences. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.funeco.2019.100864. References Albertsen, A., Ravnskov, S., Green, H., Jensen, D.F., Larsen, J., 2006. Interactions between the external mycelium of the mycorrhizal fungus Glomus intraradices and other soil microorganisms as affected by organic matter. Soil Biol. Biochem. 38, 1008e1014. https://doi.org/10.1016/j.soilbio.2005.08.015. Alexander, I., Lee, S., Burslem, D., Pinard, M., Hartley, S., 2005. Mycorrhizas and ecosystem processes in tropical rain forest: implications for diversity. In: Biotic Interactions in the Tropics: Their Role in the Maintenance of Species Diversity, pp. 165e203. Baggi, G., 2000. Ecological implications of synergistic and antagonistic interactions among growth and non growth analogs present in mixture. Ann. Microbiol. 50, 103e116. Bastian, F., Bouziri, L., Nicolardot, B., Ranjard, L., 2009. Impact of wheat straw decomposition on successional patterns of soil microbial community structure. Soil Biol. Biochem. 41, 262e275. Berg, B., De Santo, A.V., Rutigliano, F.A., Fierro, A., Ekbohm, G., 2003. Limit values for plant litter decomposing in two contrasting soils - influence of litter elemental composition. Acta Oecol. 24, 295e302. https://doi.org/10.1016/ j.actao.2003.08.002. Blackwood, C.B., Waldrop, M.P., Zak, D.R., Sinsabaugh, R.L., 2007. Molecular analysis of fungal communities and laccase genes in decomposing litter reveals differences among forest types but no impact of nitrogen deposition. Environ. Microbiol. 9, 1306e1316. https://doi.org/10.1111/j.1462-2920.2007.01250.x. Bokulich, N.A., Subramanian, S., Faith, J.J., Gevers, D., Gordon, J.I., Knight, R., Mills, D.A., Caporaso, J.G., 2013. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 10, 57e59. Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., Fierer, N., Pena, A.G., Goodrich, J.K., Gordon, J.I., 2010. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335e336. Cheng, W., Gershenson, A., 2007. Carbon fluxes in the rhizosphere. The Rhizosphere, Ecol. Perspect. 29e54. de Boer, W., Folman, L.B., Summerbell, R.C., Boddy, L., 2005. Living in a fungal world: impact of fungi on soil bacterial niche development. FEMS Microbiol. Rev. 29, 795e811. https://doi.org/10.1016/j.femsre.2004.11.005. Driver, J.D., Holben, W.E., Rillig, M.C., 2005. Characterization of glomalin as a hyphal wall component of arbuscular mycorrhizal fungi. Soil Biol. Biochem. 37, 101e106. https://doi.org/10.1016/j.soilbio.2004.06.011. Dumbrell, A.J., Ashton, P.D., Aziz, N., Feng, G., Nelson, M., Dytham, C., Fitter, A.H., Helgason, T., 2011. Distinct seasonal assemblages of arbuscular mycorrhizal fungi revealed by massively parallel pyrosequencing. New Phytol. 190,

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