Introduction
Nitrification is a crucial aerobic process in the
nitrogen cycle on a global scale, which can reduce nitrate leaching and N2O
release in the
soil (Gao et al. 2018a). It is known that
the critical rate-limiting step of nitrification is ammonia oxidization through
ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing
archaea (AOA). For a long time, it has been considered that the former is
the only participant and the main promoter for ammonia oxidation. The dominant
position of AOB was removed when the first related archaea strain, Nitrosopumilus martimus SCM1, was
isolated from seawater at the Seattle Aquarium in 2005. Since then,
ammonia-oxidizing archaea have become a research hotspot, since these are new
nitrogen-cycling microorganisms (Könneke et al. 2005). It has also been increasingly realized that ammonia-oxidizing archaea are important functional archaea, because these promote ammonia
oxidation in the nitrogen cycle in natural environments (Hatzenpichler 2012).
Due to its unique physiology, the archaea group that
oxidizes ammonia was proposed as a new phylum, Thaumarchaeota (Wu et al.
2019). It widely exists in soils, hot springs, marine
sediments, fresh water and other environments, and is even more abundant and
more sensitive to environmental changes, when compared to AOB, in soil (Zhou et al.
2016). AOA abundance and communities are often correlated
to soil properties in agroecosystems. Some studies have shown that pH is the
dominant factor that promotes the variation of AOA community (Hu et al.
2014; Li et al. 2015). Substrate availability, such as the amount of ammonium, is also a key
driver for the richness of AOA species (Zhang et al. 2015; Norman and Barrett 2016). Soil properties, including soil moisture, temperature, and manure
use, may also influence the activity of AOA (Liu et al. 2015a; Rudisill et al. 2016; Zhang et al. 2017). Some studies have also verified that AOA are crucial
ammonia-oxidizing prokaryotes under various conditions on land, indicating that
it can play more important roles in nitrification, when compared to the
bacterial counterparts (Prosser and Nicol 2012; Zhang
et al. 2012; Liu et al. 2015b). Indeed, some debate remains on this opinion.
Fertilization is an important agricultural practice that is often
employed to improve soil nutrition and plant yield. However, it also
intensively impacts the AOA community in soil (Liu et al. 2019). Some studies showed that long-term field
fertilization can prominently change the community structure of AOB, rather
than that of archaea, in paddy soil, and that the former were more susceptible
to N, when compared to the latter, in a temperate steppe, indicating that AOB
are more important (Wu et al.
2011; Chen et al. 2013). However, some studies revealed that the long-term
application of milk vetch raised the abundance of AOA and AOB in red paddy
soil. Furthermore, the long-term application of green manures has had larger
effects on the AOA community, when compared to the AOB community, in red paddy
soil (Aalto et al.
2018; Gao et al. 2018a, b). In addition, an affinity informs the environmental cooperation between
them (Straka et
al. 2019). These results suggest that AOA plays complex roles in different
environments.
Biofertilizers are playing important roles in China's high-efficiency
chemical fertilization policy. Nitrogen-fixing bacterium,
phosphate-solubilizing bacterium and Piriformospora
indica are the three kinds of important biofertilizeres, and these have
received attention from researchers (Jayathilake et al. 2006;
Aggani 2013). However, studies on AOA communities are still rare for soils treated
with biofertilizeres. In order to determine the effects of these three
biofertilizers on its communities, a study on the response of AOA to the three
biofertilizers was performed in soils in the Swan Island organic field. These
results would provide a theoretical basis for understanding the biodiversity in
soils, and reveal the mechanism for accelerating the nitrogen cycle with
different biofertilizers.
Materials and Methods
Site
description and treatment
The test field was located on Swan Island in
Shishou City, Hubei Province, China, where a cotton-soybean rotation was in place. As the old
waterway of the Yangtze River, the location was unique due to its water erosion patterns and mud
sediments. Five treatments were set for the experiment: (1) sterile H2O,
CK; (2) nitrogen-fixing bacteria, NF; (3) phosphate-solubilizing bacteria, PS;
(4) P. indica, PI; (5) the mixture of
the three strains. MI. NF and PS were provided by our research group, and PI
was presented by Professor Kaiwen Ye from Taiwan University. The above
bacterial agents were diluted with sterile H2O before use. The
effective number of viable bacteria in the diluted liquid bacteria agent was
5.0 × l08 mL-1. The bacterial agents were sprayed at a
distance of 3 cm from the seedlings at 25 days after sowing. Three replicates were
performed for each treatment. The area of each replicate was 3×10 m2
in the field experiment, and 900 mL of bacterial solution was applied for each
replicate. The distance between the blocks was 0.5 m. The soybean sowing quantity
was 112 kg ha-1.
The experimental blocks were randomly arranged, and the methods of field
management were
based on local agricultural practices. The soil samples were collected after
the soybean was harvested. These soil samples were collected in a plum blossom shape
in each block. The 0–30 cm depth soils were collected after the removal of
stones and crop residues, and placed in a -20°C soil refrigerator for
conservation. The potted experiments were carried out at the Agricultural
Environment and Ecological Engineering Laboratory in Yangtze University. The
used pot was 25 cm in upper diameter, 20 cm in bottom diameter and 30 cm in
height. The soil of the cultivated layer (0–30 cm) in test field was placed
into the pot. The soil physical and chemical properties were as follows:
organic matter content was 16.57 g kg-1, total nitrogen amount was 1.16 g
kg-1, alkali-hydrolyzed nitrogen amount was 53.62 mg kg-1,
and soil pH was 7.65. The experimental treatment was the same as the field
experiment, and the amount of bacterial agent was 10 mL per pot. When cotyledon
was fully developed, two seedlings were preserved per pot. The field experiment
and pot experiment were sown on April 20, 2019. The samples were taken at the
maturity stage, and the seeds were tested for yield (Fehr et al. 1971). The number and dry weight of the nodule
under the three biofertilizer treatments in the pot experiment were measured
according to Yan and Han report (Yan and Han 2014).
Soil available nitrogen content
The available nitrogen
(AN) content in soil from the
field experiments was estimated using the Subbiah and Asija method (Subbiah and Asija 1956). A 2 g soil sample was placed
in the outer chamber of a clean diffusion dish. The diffusion dish was gently
rotated to make the soil sample distribution even. A 2 mL indicator solution of
H3BO3 was placed into the inner chamber of the diffusion
dish, and basic glycerin was smeared on the edge of the outer chamber and
covered with ground glass. Then, 10 mL of NaOH solution (1 M) was added through a hole on one side of the ground glass, and
the diffusion dish was covered tightly and gently rotated to cover all soil
samples with lye. Afterwards, the diffusion dish was carefully placed in a
constant temperature incubator (40 ± 1°C). After alkaline diffusion for 24 h,
the NH3 in the inner chamber was titrated with 0.025 M H2SO4 solution.
The process was repeated for three times for each sample.
Gene
amplification and sequencing of AOA
The total DNA of 0.5 g of soil sample obtained
from each field treatment was isolated using a MoBio PowerSoilTM DNA
Isolation Kit (MoBio Laboratories, Carlsbad, CA, USA). Three repeats were
performed for each treatment. A
Nanodrop ND-2000 UV–VIS spectrophotometer (NanoDrop Technologies, Wilmington,
DE, USA) and 0.8% agarose gel
electrophoresis were employed to determine the DNA quantity and quality, respectively.
The high-quality DNA was conserved at -80°C in an icebox for further analysis.
The highly variable V4 region of the bacterial 16S rRNA gene (about 250 bp) was
used for sequencing, and the primer 520F and 802R were selected to use PCR
amplification. The PCR conditions were based on those described by Francis et al. (2005). The paired-end sequencing
of bacterial amplicons was conducted on the Illumina MiSeq sequencer at
Personal Biotechnology Co., Ltd. (Shanghai, China).
Quantification
of bacterial abundance
The sequencing data were analyzed using QIIME
(v1.8.0) pipeline (Caporaso et al.
2010). The raw
reads were classified into the respective samples, according to the barcodes.
After the low-quality sequences (sequence length of < 150 bp, sequence
average Phred score of < 20, sequences with ambiguous bases and sequences
with mononucleotide repeats of > 8 bp) were filtered out (Chen and Jiang 2014),
the clean reads were obtained. The paired-end reads were assembled to use FLASH
(Magoc and Salzberg 2011). Rarefaction curves
were used to estimate the depth of the sequencing library of each soil type.
After chimera detection, the sequences were clustered into operational
taxonomic units (OTUs) at 97% sequence identity utilized UCLUST (Edgar 2010). A representative
sequence was chose from each OTU using default parameters. The OTU
classification was performed through BLAST, searching the representative
sequences set against the Greengenes database for the best hit (DeSantis et al. 2006). Then, each OTU abundance in each sample was
analyzed.
Bioinformatics
analysis
The QIIME and R packages (v. 3.2.0) were
primarily used to analyze the sequence data. The alpha diversity indices (Chao1
richness estimator, ACE metric, and Shannon diversity index) were analyzed. The
OTU richness and evenness among the samples were compared using the ranked
abundance curves. Principal component analysis (PCA) was conducted in terms of
the genus-level compositional profiles. The differences in
microbial structure among the samples were assessed using the R package “vegan”. A Venn diagram was
generated to visualize the shared and unique OTUs among samples using the R
package “VennDiagram”. The taxa abundances were compared among the samples using Metastats. Partial least squares
discriminant analysis (PLS-DA) was also introduced to determine the microbiota
changes among the samples using the R package “mixOmics” (Chen et al. 2011). The Spearman’s rank correlations between the
predominant taxa were calculated in order to perform co-occurrence analysis.
Correlations (|RHO| > 0.6 and P < 0.01)
were visualized as co-occurrence networks using Cytoscape (Shannon et al. 2003). In addition, the microbial
functions were analyzed using PICRUSt (Langille et al. 2013).
Statistical
analysis
S.A.S. 8.1 was used to perform the one-way
analysis of variance (ANOVA) and correlation analysis, and Duncan's test was
used to evaluate the significance (P <
0.05) in the ANOVA.
Results
Effects of
three biofertilizers on the content of available nitrogen
Compared to CK, the content of available nitrogen
(AN) varied to some extent in soils treated with the three biofertilizers
(Table 1). The highest AN content (106.98 mg kg-1 and 69.81 mg kg-1)
occurred in soils treated with nitrogen-fixing bacterium during the pot
experiment and field experiment, respectively, while the AN content was the
lowest (61.76 mg kg-1 and 52.84 mg kg-1) in soils treated with phosphate-solubilizing bacterium
during the pot experiment and field experiment, respectively. The content of AN
in soils treated with the nitrogen-fixing bacterium significantly increased by
50.31% in the pot experiment and 29.49% in the field experiment, when compared
to that in CK (P < 0.05). The AN
content in soils treated with the solution of phosphate-solubilizing bacterium, P.
indica, or the mixture of the
three biofertilizers increased in the pot experiment and field experiment, when
compared to CK, but the differences did not reach a significant level.
Changes in
soybean yield and nodules under different biofertilizer treatments
Table 1: The content of AN in soils treated with three
biofertilizers
|
Treatment |
Pot experiment (mg kg-1) |
Field experiment (mg kg-1) |
|
CK |
53.43 ± 0.11bc |
53.91 ± 0.15bc |
|
NF |
106.98 ± 0.32a |
69.81 ± 0.36a |
|
PS |
61.76 ± 0.52bc |
52.84 ± 0.64bc |
|
PI |
66.52 ± 0.28bc |
57.24 ± 0.45ab |
|
MI |
69.08 ± 0.13b |
61.08 ± 0.22b |
Note: 1) CK: sterile water; 2) NF:
nitrogen-fixing bacterium; 3) PS: phosphate solubilizing bacterium; 4) PI: Piriformospora
indica; 5) MI: a mixture of the three strains. Data were displayed in the
form of mean ± SD (n = 3); t tests were used to detect the difference in the
content of AN in soils treated with three biofertilizers
Table 2: Changes of soybean yield under biofertilizer treatment
|
Treatment |
Pot experiment
(per plant) |
Field experiment |
||||
|
Height (cm) |
Pod number |
Pod weight (g) |
Pod Seed number |
Yield (g) |
Yield (kg/ha) |
|
|
CK |
46.37 ± 0.92a |
7.99 ± 0.08c |
1.87 ± 0.07b |
28.26 ± 0.24c |
5.33 ± 0.05b |
2100 ± 10.53b |
|
NF |
46.58 ± 1.42a |
11.46 ± 0.05a |
2.12 ± 0.51a |
36.30 ± 0.25a |
6.08 ± 0.03a |
2250 ± 16.88a |
|
PS |
47.16 ± 1.01a |
8.02 ± 0.03b |
1.91 ± 0.02ab |
28.34 ± 0.17b |
5.36 ± 0.07b |
2130 ± 8.17b |
|
PI |
46.99 ± 0.77a |
11.12 ± 0.73a |
2.08 ± 0.09a |
35.22 ± 0.33a |
5.94 ± 0.09a |
2220 ± 21.08a |
|
MI |
48.32 ± 0.65a |
11.16 ± 0.27a |
2.22 ± 0.01a |
36.25 ± 0.47a |
6.13 ± 0.03a |
2280 ± 17.10a |
Note: 1) CK: sterile water; 2) NF:
nitrogen-fixing bacterium; 3) PS: phosphate solubilizing bacterium; 4) PI: Piriformospora
indica; 5) MI: a mixture of the three strains. Data were displayed in the
form of mean ± SD (n = 3); t tests were used to detect the difference in the
relative indexes in soils treated with three biofertilizers
Table 3: Changes
of the number and dry weight of soybean root nodule in the pot experiment
|
Treatment |
Nodule number per plant |
Dry weight of nodule per plant |
|
CK |
82.29d |
188.16d |
|
NF |
116.11a |
298.27a |
|
PS |
85.56d |
188.91d |
|
PI |
94.78c |
243.24c |
|
MI |
108.76b |
281.67b |
Note: 1) CK: sterile water; 2) NF:
nitrogen-fixing bacterium; 3) PS: phosphate solubilizing bacterium; 4) PI: Piriformospora
indica; 5) MI: a mixture of the three strains. Data were displayed in the
form of mean ± SD (n = 3); t tests were used to detect the difference in the
relative indexes in soils treated with three biofertilizers
The different biofertilizer treatments had
certain effects on soybean yield and its constituent factors (Table 2). The application of MI, NF and PI
could significantly increase the soy yield and its components (P < 0.05). Among these, MI had the
most obvious effect on the increase in soybean yield under the pot or field
experiment. Compared with CK, the soy yield increased by 15.00% in the pot
experiment and increased by 8.57% in the field experiment under MI treatment.
However, the effects of these different treatments on plant height were not
significant. The root nodule number varied between 82–116 under
the different biofertilizer treatments. The number of soybean root nodules
under NF treatment increased most significantly (P < 0.05), followed by the MI treatment and PI treatment. The
effects of the different biofertilizer treatments on root nodule weight were similar to
the number of nodules (P < 0.05).
The nodule weights/sizes were, as follows: NF > MI > PI > PS > CK.
Compared to CK, the dry weight of the root nodules in the NF treatment
increased by 58.52%. In the MI treatment, the dry weight of the root nodules
increased by 49.70%. In the PI treatment, the dry weight of the root nodules
increased by 29.27% (Table 3).
Analysis of
the valid sequences of ammonia-oxidizing archaea under different treatments
The paired-end sequencing of DNA fragments from
the community of ammonia-oxidizing archaea in soils treated with the three
biofertilizers was conducted using the Illumina MiSeq platform. After removing
the low-quality sequences, the sequence length of each sample was counted
(Table 4). The statistics of length distribution of the sequences revealed that
the length was distributed between 300 bp and 400 bp (Fig. 1A). The rarefaction
curves revealed that the sequencing number exceeded 40,000, and the whole curve
tended to be flat, indicating that the sampling was reasonable, and that the
sequencing library of each soil sample reached saturation. Thus, this could
truly reflect the ammonia-oxidizing archaea groups in the soil samples (Fig.
1B).
Analysis of OTUs and venn
graph of ammonia-oxidizing archaea under different
treatments
After removing the rare OTUs and OTUs with a
abundance value lower than 0.001% of the total sequencing volume of all
samples, the remaining OTUs were identified (Table 5). The number of effective
sequences obtained was within the range of 62,681–76,897, and the number of
effective OTUs under the NF treatment was the highest under different taxon
levels. According to the obtained
OTU abundance matrix, the number of OTUs shared among the samples was
calculated, and a Venn graph was drawn (Fig. 2A). The results revealed that the
shared OUT number among all the treatments was 4,297. The unique OUT number in
the CK, NF, PS, PI and MI treatments were 25, 11, 15, 20 and 57, respectively. The
unique OTU number in
Table 4: Analysis of the sequencing amount of ammonia-oxidizing
archaea in soils treated with different biofertilizers
|
Treatment |
Sequencing
amount |
|
NF1 |
68287 |
|
NF2 |
66110 |
|
NF3 |
62720 |
|
PS1 |
57488 |
|
PS2 |
62677 |
|
PS3 |
67878 |
|
PI1 |
62737 |
|
PI2 |
61262 |
|
PI3 |
75889 |
|
MI1 |
76449 |
|
MI2 |
80373 |
|
MI3 |
73871 |
|
CK1 |
63934 |
|
CK2 |
69970 |
|
CK3 |
71124 |
Note: NF: Nitrogen-fixing
bacterium; PS: phosphate solubilizing bacterium; PI: Piriformospora indica; MI: their mixture and CK: sterile water
Table 5: Analysis of OTU classification
|
Treatment |
Sequence number |
Phylum |
Class |
Order |
Family |
Genus |
Species |
Unclassified |
|
NF |
65705.67 |
6016.00 |
5991.33 |
6006.67 |
6006.00 |
3991.00 |
6033.00 |
0 |
|
PS |
62681.00 |
5909.33 |
5887.67 |
5899.67 |
5898.33 |
3910.33 |
5925.67 |
0 |
|
PI |
66629.33 |
5908.67 |
5869.33 |
5890.33 |
5888.33 |
3852.00 |
5924.00 |
0 |
|
MI |
76897.67 |
5662.67 |
5630.67 |
5647.67 |
5647.00 |
3767.33 |
5678.67 |
0 |
|
CK |
68342.67 |
5931.33 |
5908.33 |
5920.67 |
5919.33 |
3859.67 |
5947.67 |
0 |
Note: NF: Nitrogen-fixing bacterium; PS: phosphate solubilizing bacterium; PI: Piriformospora
indica; MI: their mixtur and CK: sterile
water
%2033-42_files/image002.jpg)
Fig. 1: Assessment of the sequencing data of ammonia-oxidizing archaea in
soils treated with different biofertilizers. A. Distribution of
sequence length, B. Rarefaction
curves. NF: Nitrogen-fixing bacterium; PS: phosphate-solubilizing bacterium;
PI: Piriformospora indica; MI: their mixture and CK: sterile water
the MI treatment was
higher than that in the CK.
Diversity of
ammonia-oxidizing archaea
In order to compare the ammonia-oxidizing archaea diversity in different
soil samples under different biofertilizer treatments, a random resample was
initially made for each sample in the matrix of the OTU abundance at the depth
level of the minimum sequencing (90%) to revise the diversity differences
generated by the sequencing depth. Then, the QIIME software was used to
calculate the chao1, ACE and Shannon diversity indices for each sample (Table
6). There was no difference in the Shannon index in soils among the different
bacterial fertilizer treatments and control. Furthermore, the MI treatment had
higher Chao1 and ACE indices, when compared to the control, and there was a
significant difference from the control. The other treatments had lower Chao1
and ACE index values, when compared to the control. The PS treatment and PI
treatment had significant differences, when compared to the control. In
conclusion, MI treatment can significantly increase the AOA diversity in soil.
Taxonomic
composition analysis of ammonia-oxidizing archaea
According to the OTU identification, the specific
composition of ammonia-oxidizing archaea from each soil sample can be obtained
at different classification levels. However, the composition is not different
at the phylum, class, order and family level, while there were some differences
at the genus and species level (Table 7). Furthermore, Nitrososphaera was dominant at the genus level in the different
soil samples, and Nitrosopumilus, Candidatus Nitrosotalea and Candidatus Nitrosoarchaeum were relatively
disadvantaged. In addition, other genera were identified (Fig. 2B). The heat
map analysis also revealed that the abundance of Nitrososphaera in samples treated with NF, PI and MI increased,
when compared to that in CK (Fig. 3A).
Analysis of the AOA communities under different
treatments
Table
6: Diversity of
ammonia-oxidizing archaea communities in soil treated with different microbial
fertilizers
|
Treatment |
Shannon |
Chao1 |
ACE |
|
CK |
10.74 ± 0.04a |
4930.92 ± 68.66b |
5041.49 ± 63.19b |
|
NF |
10.92 ± 0.07a |
4782.62 ± 37.17bc |
4818.54 ± 17.5bc |
|
OP |
10.85 ± 0.04a |
4688.98 ± 56.54cd |
4711.59 ± 78.49cd |
|
PI |
10.75 ± 0.11a |
4532.53 ± 108.77cd |
4504.38 ± 97.6d |
|
MI |
10.89 ± 0.04a |
5350.93 ± 52.41a |
5336.21 ± 74.83a |
Note: 1) CK: sterile water; 2) NF:
nitrogen-fixing bacterium; 3) PS: phosphate solubilizing bacterium; 4) PI: Piriformospora indica; 5) MI: a mixture
of the three strains. Data were displayed in the form of mean ± SD (n = 3); t
tests were used to detect the difference in the relative indexes in soils
treated with three biofertilizers
%2033-42_files/image004.png)
Fig. 2: Analysis of ammonia-oxidizing archaea groups in soils treated with
different biofertilizers. A. Venn
graph of ammonia-oxidizing archaea groups. B.
The relative abundance of ammonia-oxidizing archaea at the genus level. NF:
Nitrogen-fixing bacterium; PS: phosphate-solubilizing bacterium; PI: P.
indica; MI: their mixture and CK: sterile water
Principal component analysis (PCA) was used to o
assess differences in the AOA composition in soil under different treatments.
The results showed the significant clustering of AOA communities (Fig. 3B). PC1
and PC2 explained 99.48 and 0.45% of the total changes, respectively. NF, PS,
PI and MI were obviously distinguished from CK, suggesting that there were
significant influences from the different treatments on soil AOA. Furthermore,
the community difference between PI and CK was the largest, while that between
PS and CK was the smallest. The community differences for MI or PS were
relatively small, when compared to CK. a PLS-DA discrimination model was
established according to the species abundance matrix and sample grouping data
for AOA using the R software. The results revealed that the classification
models for PI, CK and PS performed well, while those for NF and MI did not
perform well (Fig. 4A). Among these,
the classification model for PI was the best, and was quite different from CK, suggesting that the community
difference between PI and CK is significant.
Table 7: Statistical table of microbial groups at each
classification level
|
Sample |
Phylum |
Class |
Order |
Family |
Genus |
Species |
|
NF |
2 |
2 |
3 |
3 |
5 |
13 |
|
NF |
2 |
2 |
3 |
3 |
4 |
10 |
|
NF |
2 |
2 |
3 |
3 |
4 |
10 |
|
PS |
2 |
2 |
3 |
3 |
5 |
11 |
|
PS |
2 |
2 |
3 |
3 |
5 |
12 |
|
PS |
2 |
2 |
3 |
3 |
5 |
12 |
|
PI |
2 |
2 |
3 |
3 |
5 |
12 |
|
PI |
2 |
2 |
3 |
3 |
5 |
13 |
|
PI |
2 |
2 |
3 |
3 |
5 |
13 |
|
MI |
3 |
2 |
3 |
3 |
5 |
17 |
|
MI |
2 |
2 |
3 |
3 |
5 |
10 |
|
MI |
2 |
2 |
3 |
3 |
5 |
12 |
|
CK1 |
2 |
2 |
3 |
3 |
5 |
11 |
|
CK2 |
2 |
2 |
3 |
3 |
5 |
11 |
|
CK3 |
2 |
2 |
3 |
3 |
5 |
12 |
Note: NF:
Nitrogen-fixing bacterium; PS: phosphate
solubilizing bacterium; PI: Piriformospora indica; MI: their mixture
and CK: sterile water
%2033-42_files/image006.png)
Fig. 3: The relative
abundance of ammonia-oxidizing archaea in the soil at the genus level.
A. Heat map of the genus level. B. PCA analysis of the structural
similarity. NF: Nitrogen-fixing bacterium; PS: phosphate-solubilizing
bacterium; PI: Piriformospora indica; MI: their mixture and CK: sterile
water
%2033-42_files/image008.png)
Fig. 4: Comparative analysis of the AOA colony and screening of
their key species. A. PLS-DA discriminant analysis. B. The nodes represent the dominant
genera and are marked with different colors. The connections between the nodes
indicate the correlation between the two genera; a red line indicates a
positive correlation, and a green line indicates a negative correlation. The
more connections there are through a node, the more associations the genus has
with other members of the community. NF (ON): Nitrogen-fixing bacterium; PS
(OP): phosphate-solubilizing bacterium; PI (OPr): Piriformospora indica;
MI: their mixture (ONPPr) and CK (O): sterile water
%2033-42_files/image010.jpg)
Fig. 5: Map of the
evolution and abundance of AOA species. The pie chart of each branch node of the
classification showed the abundance of this taxon in each sample. The larger
the sector area is, the higher the abundance in the corresponding sample.
Analysis of
the correlation network among the dominant species of AOA
In terms of the abundance distribution of OTUs or
taxa in the different soil samples, AOA groups that were
negatively or positively correlated with each other can be found, and an
association network of the dominant AOA groups can be built to analyze the
ecological significance of the correlation (Fig. 4B). In the present study,
with the use of the Mothur software, the Spearman’s correlation coefficient was
calculated between the dominant genera, in which the abundance was within the
top 50. The correlation network was constructed for the dominant genus with an
abundance of rho of > 0.6 and a P-value of < 0.01, and the correlation
network was imported into the Cytoscape software for visualization. The results
revealed a positive correlation between Candidatus, Nitrosotalea and Nitrosopumilus, which indicating that
there was a cooperative relationship between these. However, the correlation
networks between the other dominant genera were relatively low.
Phylogenetic
analysis of AOA communities
In the process of OTU identification, the
phylogenetic tree that represented the sequence of OTUs was constructed using the Fast Tree tool. Using the MEGAN software, the OUT abundance and composition data in each soil
sample were mapped to the classification hierarchy tree provided by the NCBI
Taxonomy. The result revealed that ammonia-oxidizing archaea mostly belonged to
Thaumarchaeota (including Nitrosopumilales,
Nitrososphaeria and unidentified
Thaumarchaeota), followed by Crenarchaeota. In addition, there were some
unknown archaea (Fig. 5).
Discussion
Nitrification is an important part of the process of the nitrogen
cycle, and is closely correlated to nitrogen availability (Galloway 2008). Ammonia oxidation is the rate-limiting step of
nitrification and plays a crucial role in soil nitrogen cycle. Therefore, as
the main contributor to ammonia oxidation, AOA in soil has been a hotspot in
agricultural ecosystem research. The ammonia-oxidizing archaea in soils treated
with different biological fertilizers at the soybean seedling stage were
analyzed in the present study. The results showed that the content of available
nitrogen in soil was the highest under the treatment of nitrogen-fixing
bacterium in the pot experiment and field experiment, and this followed by MI
and P. indica. The application of MI,
NF and PI can significantly increase the soy yield and its components. The
number of soybean root nodules under NF treatment increased most significantly,
followed by the MI treatment and PI treatment. The effects of the different biofertilizer treatments on root
nodule weight were similar to the number of nodules. These results revealed that the biofertilizer has important effects
on the nitrogen fixation capacity of soils (Chakraborty and Tribedi 2019). These promote the uptake and utilization of
nitrogen by plants, and ultimately promote the formation and development of
seeds. So, do these biofertilizers
have an effect on the ammonia-oxidizing archaea in the soil?
In fact, the community
composition of AOA in soil is influenced to different extent by the applied
fertilization treatments. For example, the long-term chemical fertilization had
significant effects on the community composition of AOA in soil (He et al. 2007). However, organic
fertilization had little effects on AOA (Wang et al. 2014; Tao et al.
2017). In this study, the changes in
ammonia-oxidizing archaea in soil under different bacterial fertilizer
treatments were analyzed using high-throughput sequencing technology. The
results revealed that the number of unique OTUs in the MI treatment was the
highest among all treatments. The Chao1 and ACE indices focus on the analysis
of community richness (Chao 1984; Chao and Yang 1993). Compared to the control, the single-bacteria
fertilizer treatments had little effect on the Chao1 and ACE indices,
suggesting the stability of the soil community richness. However, the mixed
bacterial fertilizer greatly influenced the Chao1 and ACE indices. The effects
of all kinds of treatments on the Shannon index were evaluated as community
evenness, and the results were similar to those for the Chao1 and ACE indices.
These results suggest that mixed biofertilizer might
better improve the community richness and evenness, when compared to
single-bacteria fertilizers. These differences from the applied fertilization
treatments could be closed relative to the different soil conditions and
fertilezer varieties.
Archaea are important
components of complicated microbiomes in the holobiont environment. These
interplay closely with viruses, microorganisms and holobionts, such as plants
and animals (Moissl–Eichinger et al. 2018). Therefore, the changes in
microbe species in soil must influence archaea, to some extent. These present
results revealed the changes in archaea taxa at the genus and species level.
Furthermore, Nitrososphaera
was dominant at the genus-level in the different soil samples, implying the
greater functional importance of the Nitrososphaera
group, when compared to other archaea, in the present study. The heatmap
analysis also revealed that different bacterial fertilizer treatments may
influence the soil microbe species. These results are consistent with the
report of Wu et al. (2019). In addition, the correlation network analysis result
revealed that Candidatus Nitrosotalea
and Nitrosopumilus were positively
correlated. Therefore, on the basis of this study, it is very sinificant to
analyze the interaction between the dominant archaea group and three
bio-bacterial fetilizers in soil.
Conclusion
Overall, the NF, PI and MI treatments were not only beneficial for
increasing the soybean yield, but also the growth and development of soybean
root nodules. the MI treatment
significantly increased the diversity of AOA in soil. The composition of AOA
was only somewhat different at the genus and species level under different
biofertizer treatments. In addition, Nitrososphaera was dominant at the genus
level among the different soil samples. The communities in soil treated with
nitrogen-fixing bacterium and the mixture of nitrogen-fixing bacterium (MI) were
different from that in sterile water.
These results confirmed that different biofertizers could influencd the
diversity of AOA. However, the interactive mechanisms between these biofertilizers and the dominant
group of ammonia-oxidizing archaea are not elucidated well at present. Therefore, these
research on ammonia-oxidizing
archaea in soil needs to be further enhanced in the future in order to lay the
foundation for the effective utilization of biofertilizers.
Acknowledgements
We acknowledge the financial
supports of the organic agriculture development program by the Worldwide Fund
for Nature and Rare Conservation under Grant No. PO2893 and No. PO3042.
Author Contributions
Yazhen Yang and Jianqiang
Zhu conceived and designed the experiments; Mingke Fang and Yazhen Yang
performed the experiments; Meiyan Wu and Jun Hou analyzed the data, Yazhen Yang
wrote the manuscript. Jianqiang Zhu revised the manuscript. All authors read and approved the
final draft.
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