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Fungal community composition in soils subjected to
long-term chemical fertilization is most influenced by
the type of organic matter
Ruibo Sun,
1
Melissa Dsouza,
2,3
Jack A. Gilbert,
2,3,4
Xisheng Guo,
5
Daozhong Wang,
5
Zhibin Guo,
5
Yingying Ni
1
and Haiyan Chu
1
*
1
State Key Laboratory of Soil and Sustainable
Agriculture, Institute of Soil Science, Chinese Academy
of Sciences, East Beijing Road 71, Nanjing 210008,
China.
2
Marine Biological Laboratory, University of Chicago,
Woods Hole, MA 02543, USA.
3
Department of Surgery, University of Chicago,
Chicago, IL 60637, USA.
4
Argonne National Laboratory, Institute for Genomics
and Systems Biology, Argonne, IL 60439, USA.
5
Key Laboratory of Nutrient Cycling and Resources
Environment of Anhui Province, Soil and Fertilizer
Research Institute, Anhui Academy of Agricultural
Sciences, South Nongke Road 40, Hefei 230031,
China.
Summary
Organic matter application is a widely used practice
to increase soil carbon content and maintain soil fer-
tility. However, little is known about the effect of
different types of organic matter, or the input of exog-
enous species from these materials, on soil fungal
communities. In this study, fungal community com-
position was characterized from soils amended with
three types of organic matter over a 30-year fertiliza-
tion experiment. Chemical fertilization significantly
changed soil fungal community composition and
structure, which was exacerbated by the addition of
organic matter, with the direction of change influ-
enced by the type of organic matter used. The
addition of organic matter significantly increased soil
fungal richness, with the greatest richness achieved
in soils amended with pig manure. Importantly, fol-
lowing addition of cow and pig manure, fungal taxa
associated with these materials could be found in the
soil, suggesting that these exogenous species can
augment soil fungal composition. Moreover, the addi-
tion of organic matter decreased the relative
abundance of potential pathogenic fungi. Overall,
these results indicate that organic matter addition
influences the composition and structure of soil fun-
gal communities in predictable ways.
Introduction
Soil organic carbon (SOC), which is the main constituent of
soil organic matter (SOM), forms the basis of soil fertility and
sustainable agriculture. Therefore, it is one of the most
important indicators of soil quality and productivity (Reeves,
1997; Chan, 2008; Victoria et al., 2012). Intensive agricultur-
al activity greatly reduces SOC content, which in turn leads
to soil degradation (Gami et al., 2009; Victoria et al., 2012;
Olson, 2013; Stockmann et al., 2013). Many modern agri-
cultural practices encourage the increase of SOC content
by either increasing carbon inputs or by lowering losses
(Chan, 2008; Victoria et al., 2012). For this, a wide range of
organic materials such as straw, compost, organic waste,
biochar, and manure are applied to soils to increase carbon
input (Chan, 2008; Bo _
zena Cwalina-Ambroziak, 2009;
Victoria et al., 2012). But the formation of SOM depends
on the biological, chemical, and the physical decay of these
materials (Victoria et al., 2012; Stockmann et al., 2013).
Fungi are one of the most abundant soil microbes. They
serve as important decomposers in soil ecosystems, and
are typically associated with carbon sequestration in agro-
ecosystems (Hoorman, 2011; Jones et al., 2011). Studies
have shown that the diversity and distribution of soil fungal
communities are significantly related to the soil carbon
content, and that fertilization could impact soil fungal com-
munities by changing soil nutritional status and plant
biomass and physiology (Allison et al., 2007; Bo_
zena
Cwalina-Ambroziak, 2009; Weber et al., 2013; Liu et al.,
2015; Song et al., 2015; Zhou et al., 2016). For example,
N amendments decreased the relative abundance of Basi-
diomycota in an alpine tundra soil, but increased the
relative abundance of Ascomycota by 30% (Nemergut
Received 15 April, 2016; revised 17 July, 2016; accepted 26
August, 2016. *For correspondence. E-mail hychu@issas.ac.cn;
Tel. 86-25-86881356; Fax 86-25-86881000.
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Environmental Microbiology (2016) 00(00), 00–00 doi:10.1111/1462-2920.13512
et al., 2008). A similar result was observed in a silty-clay
loam in Australia, wherein applying large quantities of N
fertilizer resulted in the high relative abundance of Asco-
mycota (Paungfoo-Lonhienne et al., 2015). The overall
diversity of soil fungal communities decreased on amend-
ment with chemical fertilizers (Allison et al., 2007;
Beauregard et al., 2010; Kamaa et al., 2012). Like chemi-
cal fertilizers, the application of organic matter can also
impact soil fungal communities, with their application fre-
quently causing increased soil fungal diversity (Cwalina-
Ambroziak and Bowszys, 2009; Kamaa et al., 2012; Song
et al., 2015). These changes to soil fungal communities
are associated with the alteration of soil nutrients and plant
carbon inputs (Allison et al., 2007; Song et al., 2015). For
example, Yu and colleagues (2013) found that amendment
with Protamylasse altered pea root-fungal community
structure by favoring obligate biotrophic fungi such as Olpi-
dium brassicae, and reducing the abundance of facultative
biotrophs such as Fusarium oxysporum.
Soil fungi also play an important role in plant health.
Over 90% of all plant species can form a mycorrhizal sym-
biosis, and plant–fungus association can greatly contribute
to plant growth, persistence, community diversity, and pro-
ductivity in ecosystems (Bonfante, 2003; Lin et al., 2012).
Arbuscular mycorrhizal fungi (AMF) are frequently associ-
ated with plants, and play essential roles in nutrient
uptake, especially phosphorus. Studies have found that
chemical fertilizers decreased the diversity and coloniza-
tion rate of AMF (Lin et al., 2012; Sheng et al., 2013; Chen
et al., 2014; Song et al., 2015), while organic matter indu-
ces greater diversity and the development of external AMF
mycelium (Gryndler et al., 2006; Wu et al., 2010; Sousa
et al., 2012). The addition of nitrogen always enhances the
growth of saprotrophic fungi, and stimulates the decompo-
sition of organic substrates by saprotrophic fungi (Allison
et al., 2009; Rousk and Baath, 2011). Song and col-
leagues (2015) also found that chemical fertilization
significantly increased the diversity of saprotrophic fungi.
Hyphael extension and their ability to translocate carbon,
nitrogen and phosphorus are part of the important role of
saprotrophic fungi in nutrient and water redistribution in soil
(Crowther et al., 2012; Guhr et al., 2015), thus the growth
of plants may be supported by increasing the soil nutrient
pool and soil moisture levels (Ellouze et al., 2014). Howev-
er, chemical fertilizers have been linked to an increase in
the proportion of fungi that are pathogenic to plants
(Cwalina-Ambroziak et al., 2010; Paungfoo-Lonhienne
et al., 2015). In contrast, the application of organic matter
can suppress pathogenic fungal growth, and enhances the
growth of fungi that antagonize these pathogenic species
(Hoitink and Fahy, 1986; Gamliel and Stapleton, 1993;
Bulluck et al., 2002; Zinati, 2005; Bo_
zena Cwalina-
Ambroziak, 2009; Cwalina-Ambroziak et al., 2010; Mokhtar
and El-Mougy, 2014; Saxena et al., 2015). For example,
Cwalina-Ambroziak and Bowszys (2009) found that the
aqueous extracts from compost inhibited mycelium growth
in pathogens such as Botrytis cinerea,Colletotrichum
coccodes, and those of the genus Fusarium.
The changes of fungal community caused by organic
fertilization are due not only to the input of substrates, but
also the existing microorganisms present in the organic
matter. The latter could result in biological invasion, which
is a great threat to biodiversity and ecosystem processes
(Charles and Dukes, 2008; Ehrenfeld, 2010; Ziska et al.,
2011; Powell et al., 2013; Walsh et al., 2016). Invasive
plants and animals have been extensively studied, and
recently research has started to focus on invasive
microbes, especially fungi, which are extremely important
in driving plant diversity and productivity (van der Heijden
et al., 2008). Non-indigenous fungal pathogens have great-
ly reduced the population sizes of several native tree
species in North America (Loo, 2008). Day and colleagues
(2015) revealed that the fungi associated with non-native
plants could benefit the growth of these plants by causing
disease in native plants and thereby affecting their growth.
Additionally, invasive fungi have a significant detrimental
effect on agricultural ecosystems (Rossman, 2009). Man-
ures used for agricultural production may also contain
microbial pathogens that pose a threat to human health
(Unc and Goss, 2004; Gerba and Smith, 2005; Mosadde-
ghi et al., 2010; Bradford et al., 2013).
Although the impact of fertilization on soil fungal commu-
nities has been extensively studied, the long-term effects
of different types of organic matter remain unknown. Previ-
ous research provided evidence for differing carbon
sequestration efficiencies for soils amended with wheat
straw, and cow and pig manure (PM) (Hua et al., 2014),
which is likely to be mediated by different fungal taxa tar-
geting different organic compounds (Hanson et al., 2008).
We hypothesize that different organic matter will select for
different soil fungal communities. In addition, multiple fungi
have been detected in organic material, but the impact of
exogenous fungi associated with the organic material on
native soil fungal communities is rarely explored (Anastasi
et al., 2005; Fliegerov
aet al., 2010; Lopez et al., 2014). To
address this gap, we utilized high-throughput amplicon
sequencing to compare fungal communities of soils sub-
jected to long-term chemical fertilization (NPK) amended
with low- or high-levels of wheat straw residues (S), cow
manure (CM), and PM together with the fungal community
associated with this manure.
Results
Changes in soil fungal community under different
fertilization regimes
Approximately 1.2 million raw internal transcribed spacer
region 1 (ITS1) amplicon reads were obtained for 24 soil
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samples and 2 manure samples. After quality filtering,
812,748 (20,277–51,140 reads per sample) reads were
used for all downstream analysis. These high-quality reads
were clustered in to 997 non-singleton operational taxo-
nomic units (OTUs), with a large majority being assigned
to the phylum Ascomycota (80.7% of all reads). Basidio-
mycota and Zygomycota accounted for 13.8% and 3.1% of
reads respectively (Fig. 1A).
Fungal a-diversity was determined by the Chao1 rich-
ness index and the Heip’s evenness index, both calculated
with 20,000 rarefied sequences per sample (Heip, 1974;
Gotelli and Colwell, 2011). Good’s coverage was deter-
mined to estimate sampling completeness (Good, 1953;
Rea et al., 2011). Good’s coverage values (at the 97% sim-
ilarity level) were greater than 0.995 for all treatment types,
indicating that the vast majority of the fungal community
was captured at this sequencing depth (Table 1). The
lowest Chao1 richness index was observed for control
soils. No significant difference for Chao1 was observed
between NPK and control soils (Mann-Whitney U57.00,
P>0.05). However, significant differences were observed
between control soils and those amended with different
organic materials (Value of Mann-Whitney U was 0
between organic material amended treatments and control
treatment, P<0.05). The amended soils showed signifi-
cantly higher fungal richness compared to controls. In
contrast, Heip’s evenness was greatest in control soils,
although not significantly so. Of all treatment types, the
NPK 1PM soils showed the highest fungal richness and
the lowest fungal evenness (Table 1).
Fertilization greatly influenced the soil fungal community
structure. The taxonomic distribution of soil fungi changed
under different treatment types. At the phylum level, NPK,
NPK 1LS, and NPK 1HS fungal profiles were more
Fig. 1. Taxonomic composition of soil fungal communities by the different treatment regimes at the phylum (A) and the class level (B). PCoA
plot depicts the Bray–Curtis distance of fungal communities in 24 soil samples under the six treatment regimes (C). The red ellipses in this
plot represent the confidence areas (0.95) of the treatment. The blue dotted lines enclose the convex hull for the samples in the same
treatment. The blue lines combine samples to their class centroid. Control, non-fertilization; NPK fertilization; NPK with low-level wheat straw
(NPK1LS); NPK with high-level wheat straw (NPK1HS); NPK with PM (NPK1PM); and NPK with CM (NPK1CM).
Fertilizer organic matter influences soil fungal community 3
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similar to the control samples than NPK 1PM and
NPK 1CM samples. The fungal community composition
was significantly different between NPK 1PM, NPK 1CM
and the control samples (Fig. S2). NPK1PM and
NPK 1CM samples had a greater relative abundance of
Zygomycota as compared to the control samples (Fig. 1A).
The relative abundance of dominant taxa also changed
under the different treatments regimes (Fig. 1B and Sup-
porting Information Fig. S1). Three taxa were closely
related to Stagonosporopsis crystalliniformis (OTU3406),
Alternaria alternate (OTU5521), Fusarium circinatum
(OTU2170), which are known plant pathogens (Supporting
Information Table S1) (Peever et al., 2002; Wingfield et al.,
2008; Vaghefi et al., 2012). The relative abundance of
these OTUs were much greater in the control and/or NPK
samples compared to those amended with organic materi-
als, and in particular those samples amended with cow
and PM (Supporting Information Fig. S1). The changes in
soil fungal communities were further depicted in the two-
dimensional principal coordinate analysis (PCoA) plot
using Bray-Curtis distance (Fig. 1C). Soils that were only
subjected to chemical fertilizers (NPK) clustered with con-
trol soils that received no treatment (Fig. 1C). In contrast,
soils amended with the different organic materials clus-
tered away from the control soils. While separate clusters
were observed for NPK 1PM and NPK 1CM samples,
the two wheat straw treatment types, NPK 1LS and
NPK 1HS clustered together. These results indicated that
long-term chemical fertilization describes less of the vari-
ance in soil fungal community structure than the
amendment of soil with different organic materials. Addi-
tionally, soil fungal communities tended to distribute
according to the type of organic material added (Fig. 1C).
This was confirmed by analysis of similarity (ANOSIM) cal-
culation (Supporting Information Table S3). Similar
observations of clustering by treatment type were made by
the hierarchical clustering tree method (Supporting Infor-
mation Fig. S2A).
Indicator species by treatment type
Indicator species were determined by the Dfrene-
Legendre indicator species analysis method (Dufrene and
Legendre, 1997) to identify fungal OTUs that are specifi-
cally associated with the different treatment regimes.
Indicator species (OTUs) for each treatment type are pre-
sented in Fig. 2. Additional information on taxonomic
assignment of indicator species by treatment type is pre-
sented in Supporting Information Table S1.
OTU3406 was the most abundant indicator species in
the control samples with a relative abundance of 8.42%,
and was most closely related to Stagonosporopsis crystal-
liniformis CBS 713.85, which is a foliage pathogen of
potatoes (Solanum tuberosum) and tomatoes (S. lycoper-
sicum), causing ‘black potato blight’ and ‘carate’ on
tomatoes (de Gruyter et al., 2012).
The most abundant indicator species in the NPK sam-
ples was OTU2166, which was most closely related to a
Hypocreales sp. It accounted for approximately one fifth of
the soil fungal community in this treatment type. Hypo-
creales spp. are widespread in moist forests, and many
Hypocreales species grow on wood rather than herba-
ceous substrata, and parasitize other fungi, such as
Ascomycota, resupinate Basidiomycetes, and perennial
bracket fungi (Chaverri and Samuels, 2003). Hypocreales
spp. have antifungal activity, thus making them potentially
valuable in the biological control of fungal diseases (Cha-
verri and Samuels, 2003). The high relative abundance of
these pathogen-antagonists is usually indicative of the
presence of the pathogens themselves. This was sup-
ported by the high relative abundance of another indicator
species, OTU2170 (8.52%), which was most closely relat-
ed to Fusarium circinatum (Supporting Information Table
S2), which is known to cause a destructive disease of
pines - pitch canker (Wingfield et al., 2008). A similar result
was observed for the control samples where OTU2166
(Hypocreales sp.) and OTU3406 (Stagonosporopsis
Table 1. Fungal diversity by treatment type and manure.
Treatment
Diversity index
Chao1 richness index Heip’s evenness index Good’s coverage
Control 300(13)c 0.134(0.021)a 0.997(0.000)a
NPK 313(33)bc 0.105(0.013)ab 0.997(0.001)ab
NPK1LS 348(50)ab 0.102(0.018)ab 0.996(0.001)c
NPK1HS 380(45)ab 0.12(0.02)a 0.996(0.001)c
NPK1PM 388(22)a 0.08(0.02)b 0.995(0.000)d
NPK1CM 344(11)b 0.124(0.009)a 0.997(0.000)b
Pig manure 284 0.098 0.998
Cow manure 193 0.009 0.998
The diversity indices were calculated using 20,000 randomly selected sequences per sample. Means of four replicates per treatment are pre-
sented (with standard deviation).
Data containing the same letter within a column indicate no significant difference between treatments detected by Mann-Whitney U test
(P>0.05).
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crystalliniformis CBS 713.85) were abundant (Supporting
Information Fig. S1).
The most abundant indicator species in the wheat straw
amendment samples was OTU5031, which was most
closely related to Chaetomium globosum (Supporting
Information Table S2), a saprophytic fungus primarily resid-
ing on plants, soil, straw, and dung. It possesses a
cellulose-degrading system (Longoni et al., 2012) and can
produce antifungal compounds to antagonize spot blotch
(Cochliobolus sativus) and leaf rust (Puccinia recondita)of
wheat, as well as rice blast (Magnaporthe grisea)(Aggar-
wal et al., 2004; Park et al., 2005).
OTU3457 (most closely related to Pseudaleuria sp.) with
a relative abundance of 17.07% was the most abundant
indicator species in the NPK 1PM samples. Xu and col-
leagues (2012) demonstarted that Pseudaleuria were
dominant in healthy soils, and were negatively correlated
with the disease severity index of pea roots. Finally, indica-
tor species OTU1561, which accounted for one tenth of
the community in the NPK 1PM treatment type, had no
close match in these databases and as such may repre-
sent a novel fungal taxon.
For the NPK 1CM treatment type, OTU5240, which
was most closely related to Mortierella sp. was the most
abundant indicator (8.04%). Members of this genus pri-
marily serve as saprotrophs in soil ecosystems, typically
living on decaying leaves, fecal pellets, and other organic
material (Webster and Weber, 2007). Studies have found
that some species of Mortierella have the ability to degrade
chitin and hemicellulose (Raudonien_
e and Varnait _
e, 2008;
Young-Ju et al., 2008). Moreover, as a phosphate-
solubilizing fungus, they could help with the colonization of
AMF and alleviate the deleterious effects of salt on plant
growth and soil enzyme activities (Zhang et al., 2011).
Fig. 2. Indicator species by treatment regime. Circles represent OTUs, and the other shapes represent the different treatment regimes. The
size of each circle represents its relative abundance.
Fertilizer organic matter influences soil fungal community 5
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Fungal community composition of livestock manures
The fungal communities in pig and CMs were also charac-
terized and were largely different to those observed for
soils. Ascomycetes and Basidiomycetes were the most
abundant phyla in pig and CM samples respectively (Sup-
porting Information Fig. S3a/b). Fungal communities in
PM were dominated by seven OTUs (relative
abundance >5%), of which the most abundant (20%) was
closely related to Cladorrhinum bulbillosum.OTUsmost
closely related to Agaricales sp. (relative abundance of
85.17%) dominated CM (Supporting Information Fig. S3c).
Overall, the fungal diversity of manure was lower than that
of soil (Table 1), and both richness and evenness were
lowest in CM.
Correlations between environmental factors and fungal
community structure
Redundancy analysis explained approximately 70% of the
total variation in the soil fungal community structure, and
the first two components explained 48.96% of the variation
(Fig. 3, Supporting Information Table S6). Soil fungal com-
munities formed clusters by treatment type on the RDA
plot (Fig. 3A). Through canonical variation partitioning, it
was observed that the organic material utilized for soil
amendment was the major contributor to fungal community
variation, explaining 16.8% of the variation in soil fungal
communities (Fig. 3B).
We compared the fungal community in cow and PM to
those found in amended soils to investigate the potential
for invasion. Results showed that 113 OTUs were shared
between pig manure and soils amended with pig manure
(NPK 1PM). This accounted for 24.9% of the NPK 1PM-
associated OTUs, and of these, 28 OTUs (5.9%) were
detected in pig manure and the amended soils but not in
the control soils (Fig. 4A). These 28 OTUs accounted for
about 1% relative abundance of the NPK 1PM community.
Likewise, 76 OTUs were shared between CM samples and
soils amended with CM (NPK 1CM), which accounted for
16.4% of the total NPK 1CM-associated OTUs; and of
these, 24 OTUs were not detected in the control soils (Fig.
4B). These 24 OTUs accounted for about 0.7% relative
abundance of the NPK 1CM community. Ternary plots
showed the distribution of OTUs detected in both control
and manure-amended soils (NPK 1PM and NPK 1CM)
(Fig. 4C and D). A total of 29 OTUs were enriched in the
NPK 1PM samples as compared to the control soils, and
nine OTUs were diluted in these samples. Likewise, 23
OTUs were enriched in the NPK1CM samples and five
were diluted compared to controls. Some of the
NPK 1PM-associated enriched OTUs were abundant in
PM (Fig. 4C), suggesting the strong possibility of PM as a
source of these OTUs. In contrast, most of the NPK 1CM-
associated, enriched OTUs were not abundant in CM (Fig.
4D).
Predicted sources of fungal communities in manure
amended soils
A Bayesian probability tool, SourceTracker, was used to
predict the sources of OTUs found in manure-amended
soils. Most of the fungal community was likely sourced
from native soil (Fig. 5), which contributed between
57.93% and 78.55% on average to NPK1PM and
NPK 1CM samples respectively. Fungi in PM contributed
17.62% to the fungal community in NPK 1PM samples,
which was much greater than the contribution made by
fungi in CM to NPK1CM samples (0.54%) (Fig. 5).
Discussion
Several different types of chemical fertilizers and organic
materials have been added to soils to increase its nutrient
Fig. 3. Redundancy analysis plot depicting the correlation between fungal communities and soil properties (A), and the percentages of
variance explained by each factor (B). TOM, type of organic material; NO2
3-N, nitrate, NH1
4-N, ammonium; TN, total Nitrogen; AP, available
Phosphorus.
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Fig. 4. Venn diagrams showing the distribution of OTUs in non-fertilization treatment soils (control), soils subjected to long-term application of
NPK with pig manure (NPK1PM), and pig manure (PM) (A); and non-fertilization treatment soils (control), soils subjected to long-term
application of NPK with cow manure (NPK1CM), and cow manure (CM) (B). Ternary plots of OTUs shared between Control and NPK 1PM
(C) and OTUs shared between Control and NPK 1CM (D). The grey circles represent OTUs with no significant differences in relative
abundance between manure-amended and control soils, represents OTUs that had a significantly higher relative abundance in manure-
amended soils than control soils, and represents OTUs that had a significantly lower relative abundance in manure-amended soil than
control soils.
Fertilizer organic matter influences soil fungal community 7
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and carbon content, and particularly to improve soil fertility
and agricultural production. The impact of fertilization on soil
microbial communities is of growing concern due to the
importance of microbes in soil ecosystems. Here we
revealed that the addition of organic material had a greater
impact on fungal composition and can result in increased
fungal richness as compared to chemical fertilization. Addi-
tionally, soil amendment with different types of organic
material resulted in significantly different fungal communities.
One of the most important services performed by fungi
in a soil ecosystem is decomposition – converting various
organic materials into bioavailable forms (Hoorman, 2011).
Fungi secrete enzymes to digest complex organic com-
pounds and absorb the breakdown products. Chemical
fertilizers do not serve as a direct carbon source, but can
impact soil fungal communities by altering the amount and
quality of plant carbon inputs (Allison et al., 2007; Weber
et al., 2013). However, the impact of plant carbon inputs
was far less than that observed as a result of soil amend-
ment with organic materials. Thus, we observed a greater
shift in fungal communities in soils amended with organic
materials than those solely treated with chemical fertilizers
(Supporting Information Fig. S2b). In addition, soils
amended with the different organic materials (including
wheat straw, PM, and CM) contained different fungal com-
munities. One possible reason may be the differences in
the carbon composition of the three types of organic mate-
rial. Fungal communities are regulated by resource type
and availability (Moll et al., 2015). Although tens of thou-
sands of fungi species live in soil, different fungal taxa
possess different resource utilization capabilities, and
some of them target particular organic compounds (Hanson
et al., 2008). Fungal taxa occupy different ecological
niches according to the available carbon source. Resource
partitioning among soil fungi is considered to be an impor-
tant mechanism for the maintenance of fungal diversity in
soil ecosystems (Hanson et al., 2008). For example,
Deacon and colleagues (2006) found that fungi isolated
from grassland soils had significant variability in resource
use; 83% utilized starch, 63% pectin, 63% cellulose, and
only 27% could use lignin, while 8% used chitin. Hoppe and
colleagues (2015) found significantly different fungal com-
munity structures in the deadwood of different tree species,
and attributed these differences to the varying physiochemi-
cal properties of the deadwood substrates. In this study, we
observed that the variance in fungal communities associated
with the different treatments was best explained by the
type of organic material, suggesting differential resource
utilization capabilities. In soils amended with organic mate-
rial, the enriched OTUs were closely related to fungal taxa
that are known to possess the ability to biodegrade and
decompose organic residues. For example, the most abun-
dant indicator species in NPK 1wheat straw samples,
OTU5031 (Supporting Information Fig. S1), was closely
related to Chaetomium globosum, which degrades cellu-
lose (Longoni et al., 2012), the main component of wheat
straw (Kabuyah et al., 2012).
The application of organic material is also known to sup-
press plant pathogenic fungi. Possible suppression
mechanisms include antibiosis, competition, hyperparasit-
ism, and induced systemic resistance (Bailey and
Lazarovits, 2003; Zinati, 2005; Walters and Bingham,
2007; Mokhtar and El-Mougy, 2014). We also observed a
reduced abundance of OTUs closely related to known
plant pathogens in soils amended with organic materials.
The presence of OTUs related to Chaetomium globosum
Fig. 5. The sources of fungal community in PM (A) and CM (B) amended soils as predicted by SourceTracker.
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in wheat straw ammended soils, could suggest a potential
mechanism, as this organism can produce antifungal com-
pounds (Aggarwal et al., 2004; Park et al., 2005). A similar
observation was made by Yu and colleagues (2013)
wherein the presence of bacterial phyla including the Acid-
obacteria, Gp14, and Actinobacteria and the fungal class,
Cystobasidiomycetes played a more important role than
abiotic factors in the suppression of Pythium wilt disease.
The maintenance of high soil microbial diversity and
functional redundancy has been suggested to be a useful
for maintaining soil ecosystem health (Allison and Martiny,
2008; Sharma et al., 2011; Bhat, 2013; Miki et al., 2014).
In this study, an increase in fungal richness was observed
in soils amended with the different organic materials thus,
which could suggest that organic materials improved soil
‘health’ when compared to chemical fertilizers. Soils
amended with PM were more diverse than CM or wheat
straw amendments. The greater diversity observed in
manure amended soils may be due to the introduction of
exogenous fungi. Exogenous microbes introduced to soil
from manure have been shown to impact soil microbial
communities (Guan and Holley, 2003; Unc and Goss,
2004). While we were able to amplify ITS1 sequences
from cow and PM samples, we failed to produce any ampli-
fication in wheat straw. This could be because of PCR
amplicifcation inhibitors in the extract, or because of low
fungal biomass in wheat straw. If the latter then this would
suggest that there is limited impact of exogenous fungi
from wheat straw. Conversely, the manure-associated taxa
had an observed influence on soil fungal communities, but
for unknown reasons this was greater for pig-manure (Fig.
5, Supporting Information Tables S4 and S5). Some of
these taxa may influence soil ecological functions. For
example, OTU29 from PM was most closely related to
Acremonium alcalophilum (OTU29), which can degrade
both cellulose and xylan at temperatures as low as 08C
(Hayashi et al., 1996; Hayashi et al., 1997; Kasana and
Gulati, 2011). Additionally, OTU2781 was most closely
related to an anaerobic fungus, Buwchfawromyces eastonii
(Callaghan et al., 2015). These non-native fungi may
enhance nutrient transformation and the degradation of
organic materials under different environments including
frost and flooding. Meanwhile some OTUs were related to
taxa that could influence plant health. For example,
OTU989 from CM was closely related to Ophiocordyceps
lanpingensis, which can parasitize larval pathogens that
affect plants (Chen et al., 2013). Therefore the introduction
of this taxon could act to reduce the burden of insect
attacks. We were able to identify close relatives for many
OTUs, yet some remain unidentified; even so the ecologi-
cal role and impact of all of these organisms needs to be
characterized and validated in different ecosystem
contexts.
Conclusions
Fungi play an essential role in soil ecological processes,
especially in the degradation of organic materials. The
results from this study revealed that soil amendment with
organic materials explained patterns in soil fungal commu-
nity diversity and composition better than the use of
chemical fertilizers. The addition of organic materials
increased soil fungal richness, and lowered the relative
abundance of potentially pathogenic fungi. Interestingly
some fungi introduced to the soil from manure were closely
related to pathogen-antagonists, suggesting a potential
mechanism for pathogen suppression. Like previous
reports on long-term, chemical and organic fertilization
experiments, we also reported that cow and PMs were bet-
ter than wheat straw in improving soil physiochemical
properties, increasing crop yields, and preventing the loss
of microbial diversity (Sun et al., 2015b). This study sug-
gests that adding the type of organic matter influences the
structure and composition of the soil fungal community in
predictable ways. Understanding these influences further
could be crucial for sustainable agriculture.
Experimental procedures
Experimental design, soil sampling, determination of soil
properties, and DNA extraction
The experimental site is located at the Madian Agro-
Ecological Station in Mengcheng county, Anhui province,
China (N338130,E1168350). The experiment was started in
1982 and includes six treatments with four replicate plots for
each treatment-type. These include: (i) control (no fertiliza-
tion), (ii) chemical NPK fertilizers only (NPK), (iii) chemical
NPK fertilizers added with low amount (3750 kg ha
21
y
21
)of
wheat straw (NPK 1LS), (iv) chemical NPK fertilizers added
with high amount (7500 kg ha
21
y
21
) of wheat straw
(NPK 1HS), (v) chemical NPK fertilizers added with fresh PM
(NPK 1PM), and (vi) chemical NPK fertilizers added with
fresh CM (NPK 1CM). In October 2012, 12 soil cores (5 cm
in diameter) from the surface layer (0–10 cm) were collected
from each plot, and mixed thoroughly as a single sample. Soil
pH, total carbon (TC), total nitrogen (TN), nitrate (NO2
3-N),
ammonium (NH1
4-N), dissolved organic carbon (DOC), dis-
solved organic nitrogen (DON), available potassium (AK), and
available phosphorus (AP) were measured. DNA was
extracted from 0.5 g of fresh soil using a FastV
RDNA SPIN Kit
(MP Biomedicals, Santa Ana, CA) according to manufacturer’s
instructions. Detailed information on experimental design, soil
sampling, determination of soil properties, and soil DNA
extraction is as described previously by Sun et al. (2015b) and
Chu and Grogan (2010). Ten replicate samples (about 30 g
per sample) of wheat straw were collected prior to its applica-
tion. The wheat straw samples were cut into pieces and
ground using a ball mill (Emax, Retsch, Germany). DNA was
extracted from 0.2 g of disrupted wheat straw tissue using a
Dneasy plant kit (Qiagen, Germany) according to manufac-
turer’s instructions. Likewise, 10 replicate samples each of
cow and PMs were collected from different positions within the
Fertilizer organic matter influences soil fungal community 9
V
C2016 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology,00, 00–00
manure piles and mixed as a single sample separately before
their application. Manure samples were mixed by sterile
homogenate machine, and DNA was extracted from 0.5 g of
manure using a PowerFecalV
RDNA Isolation Kit (MO BIO,
USA) according to manufacturer’s instructions. Three repli-
cates of DNA extracts from wheat straw, pig and CM samples
were selected and pooled separately for PCR amplification.
PCR amplification and high throughput sequencing
Primers ITS1F (50-CTTGGTCATTTAGAGGAAGTAA-30) and
ITS2 (50-GCTGCGTTCTTCATCGATGC-30) (Ghannoum et al.,
2010) were used to amplify the ITS1 region, which is the uni-
versal DNA barcode marker for the molecular identification of
fungi (Schoch et al., 2012; Blaalid et al., 2013). PCR was per-
formed in 50 ll reaction volumes containing 25 ll of Premix
Taq DNA polymerase, 0.5 ll of forward primer (20 mM), 0.5
ll of reverse primer (20 mM), 23 ll of double distilled water
(ddH
2
O), and 1 ll DNA template (20 ng total soil DNA). The
PCR cycling conditions were 948Cfor5min,35cyclesof948C
for30s,at508C for 30 s, and 728C for 30 s. Illumina libraries
were constructed using the MiSeq Reagent Kit v3 according to
manufacturer’s instructions. High-throughput, paired-end
sequencing was performed on the Illumina MiSeq PE250 plat-
form. Sequencing data were deposited in the European
Nucleotide Archive under the accession number PRJEB12829.
Analysis of sequencing data
Sequencing data were processed using the QIIME software
package (version 1.9.0) (Caporaso et al., 2010). Briefly, for-
ward and reverse reads were joined using fastq-join with a
minimum of 10 bp overlap. Low quality sequences (Phred
quality score Q <20 or sequences shorter than 200 bp) were
discarded, and chimeras were filtered by the UCHIME algo-
rithm (Edgar et al., 2011) in the USEARCH tool (Edgar, 2010)
using the UNITE fungal ITS reference data set (Version 7.0)
(Nilsson et al., 2015). High-quality sequences were assigned
to OTUs using UCLUST with a similarity threshold of 97%
(Edgar, 2010). Taxonomy was assigned using the UCLUST
consensus taxonomy assigner and the UNITE fungal ITS
database (QIIME release, version 7.0) (Bengtsson-Palme
et al., 2013). OTUs with no taxonomic assignment from QIIME
were identified using blastn and the internal transcribed spac-
er region (ITS) from fungi type and reference material
database (Johnson et al., 2008; Schoch et al., 2014). Single-
tons and non-fungal OTUs were removed and all samples
were rarefied to 20 000 sequences per sample for further
analysis.
Statistical analyses
Principal coordinates analysis (PCoA) was used to compare
the beta diversity between samples based on the Bray-Curtis
distance matrix. This was performed in the R software pack-
age (version 3.1.2) using the ape library (Paradis et al., 2004).
Hierarchical clustering was determined by unweighted pair
group method with arithmetic mean (UPGMA) (Milligan, 1985)
in R using the vegan library (Oksanen, 2015). Mann-Whitney
U test was used to compare diversity indices between
treatments, as the data were not randomly distributed. ANO-
SIMs (Clarke, 1993; Warton et al., 2012) based on Bray-
Curtis distances was performed using vegan in R. Heatmaps
were drawn using gplots (Warnes et al., 2016) in R. Indicator
analysis was done using labdsv (Roberts, 2012.) in R, and
visualized using the Cytoscape package (Version 3.2.1)
(Shannon et al., 2003). Redundancy analysis (RDA) was car-
ried out to determine the effect of soil properties on the fungal
community in R using vegan. Only environmental variables
that were significantly (P<0.05) correlated with the RDA mod-
el were selected (calculated based on 999 permutations), and
the respective effects of different explanatory variables were
calculated by canonical variation partitioning (Borcard et al.,
1992; Sun et al., 2015a). The significance of RDA models
were tested by ANOVA based on 999 permutations. Ternary
plots were drawn in R using the vcd package (Meyer et al.,
2015). SourceTracker (Version 0.9.5) (Knights et al., 2011)
was used to predict the source of fungal communities in
manure-amended samples (NPK 1PM and NPK 1CM).
NPK 1PM and NPK 1CM samples were set as sink, and the
control (used as native soil) and the manure samples were set
as sources. Source predictions were run with 100 burnins, 10
random restarts, and rarefaction depth of 20 000.
Acknowledgements
We thank Congcong Shen, Xingjia Xiang and Yuntao Li for
assistance in soil sampling, and Keke Hua for the manage-
ment of the experimental field. We also thank Rong Huang for
assistance in sequencing. This work was funded by the Strate-
gic Priority Research Program of the Chinese Academy of Sci-
ences (XDB15010101), the National Program on Key Basic
Research Project (2014CB954002) and the National Natural
Science Foundation of China (41371254). The authors
declare no conflicts of interest.
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Supporting information
Additional Supporting Information may be found in the
online version of this article at the publisher’s web-site:
Fig. S1. Heatmap illustrating the distribution of the most
abundant soil OTUs (relative abundance 1.5% in any of
the treatment) by treatment type. * indicates plant patho-
genic fungi. Control, no fertilization; NPK, application of
chemical fertilizers; NPK1LS, application of chemical fertil-
izers with low amounts of wheat straw; NPK1HS, applica-
tion of chemical fertilizers with high amounts of wheat
straw; NPK1PM, application of chemical fertilizers with pig
manure; NPK1CM, application of chemical fertilizers with
cow manure. Taxonomic levels: p, phylum; c, class; o,
order; f, family; g, genus; s, species.
Fig. S2. Hierarchical Clustering of fungal communities by
treatment type (a). Bray-Curtis dissimilarity of fungal com-
munities between treatments (b). Percentage bootstrap val-
ues obtained from 1000 trials are shown on branches. *
indicates that the fungal communities were significantly dif-
ferent between treatments as detected by analysis of simi-
larities (ANOSIM) using the Bray-Curtis distance. The R
values of ANOSIM results, which were calculated based on
999 permutations, can be observed under the dissimilarity
value.
Fig. S3. Fungal community composition of pig manure (a)
and cow manure (b). Relative abundances of abundant
OTUs (relative abundance 5%) for cow and pig maure (c).
PM, pig manure; CM, cow manure.
Table S1. Indicator species of the treatments.
Table S2. BLAST results of the dominant species.
Table S3. Result (R value) of analysis of similarities (ANO-
SIM) between the different organic material treatments.
Table S4. The relative abundance of indicator species of in
NPK1PM, pig manure and control samples.
Table S5. The relative abundance of indicator species in,
NPK1CM, cow manure, and control samples.
Table S6. Results of redundancy analysis.
14 R. Sun et al.
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