KEYWORDS
saline-alkali soils, amelioration, Melia azedarach L. ,
high-throughput sequencing, microbial communities
1 INTRODUCTION
Saline-alkali soils are widespread globally, occupying about
9.5×108 ha at present (Wang et al. , 2003). In
China, the total area of saline-alkaline soils is about
3.6×107 ha, accounting for 4.88% of the available
land area in the country; importantly, nearly 7% of cultivated soils
contain excessive salt (Mao et al. , 2016). Soil salinization has
become a global concern, and it is one of the main reasons for poor crop
growth, soil desertification and ecological degradation (Pan et
al. , 2011; Singh, 2016). Saline-alkali soils are characterized by high
soil salinity, poor soil structure, sparse (if any) vegetation coverage,
and low land productivity (Wang et al. , 2011a; Zhao et
al. , 2018).
Various techniques have been used for amelioration of saline-alkali
soil, including chemical, physical, biological and engineering
improvements to increase fertility and crop yield (Liu et al. ,
2015). Deep ploughing to 30-40 cm could break the hardened soil layers
and reduce soil salinity (Riley & Ekeberg, 1998). Phytoremediation is a
biological technique that uses plants to improve saline-alkali soils
(Imadi et al. , 2016; Mishra et al. , 2002; Qadir & Oster,
2002). Using plants can effectively improve the physical and chemical
properties of saline-alkali soils, increase the stability of the
ecosystem, and enhance the carrying capacity of the environment;
notably, these phytoremediation-related improvements of saline-alkali
soils are stable and durable (Shahbaz & Ashraf, 2013).
Melia azedarach L. is an important deciduous tree species. It has
ornamental value and is widely used in making furniture, plywood and
toys as well as for firewood. In addition to the direct economic
benefits, it may be used in re-vegetation of degraded areas (Husain &
Anis, 2009). Melia azedarach L. has high medicinal value.
Flowers, leaves, fruits and root bark can be used as medicine. Studies
have shown that the extract of Melia azedarach L. leaves has
anti-cancer effects (Ervina et al. , 2020). Melia azedarach
L. has the advantages of rapid growth, strong adaptability, capacity to
grow of low-fertility soil, and strong salt resistance (Dias et
al. , 2014).
Amelioration of saline-alkali soils is contingent on improving basic
soil properties as well as enhancing the diversity of soil microbes
(Peng et al. , 2017). However, there is little research about a
role of Melia azedarach L. in improving saline-alkali soils. We
explored the potential of Melia azedarach L. to improve
saline-alkali soil by characterizing its influence on the soil chemical
properties, enzyme activities and microbial diversity to provide a
theoretical basis for saline-alkali soil remediation.
2 MATERIALS AND METHODS
2.1 Field set-up
The experimental area was located in Xu Wei New District (34°37′N,
119°29′E), located in the warm humid monsoon climate zone, with 14°C
average annual temperature, 901 mm annual average rainfall and 855 mm
annual average evaporation. Before planting Melia azedarach L. ,
field was ploughed to 30-40 cm. The size of a Melia azedarach L.planting hole was 70×70×70 cm, and the row spacing was 2×3 m. Three
replicate plots were used to sample bare soil (CK), bulk soil (BS, far
away from Melia azedarach L. roots) and rhizosphere soil ofMelia azedarach L. (RS).
2.2 Soil sample collection
In August 2019, bare soil was taken randomly in places without
vegetation to a depth of 0–20 cm using a soil auger (6 cm diameter).
After excavating the 2.5-year-old Melia azedarach roots, bulk
soil was collected far away from Melia azedarach roots, whereas
rhizosphere soil (about 1-mm-thick layer around rots) was collected
using a brush. Each sample had three biological replicates. A portion of
each soil sample was snap-frozen in liquid nitrogen and kept at -80℃ for
molecular analyses, whereas the other portion was transferred to the lab
on ice and stored at 4℃ for analysing physical and chemical properties.
2.3 Measurement of soil properties
To determine soil salinity, pH, Na, K, Ca, Mg and Cl-,
we mixed 20.0 g of soil sample with 100 mL of carbon dioxide-free water,
passed the suspension through qualitative filter paper, and collected
the filtrate for analyses. Soil salinity was determined by a
conductivity meter (FE38-Standard, Mettler Toledo, China). The soil pH
was determined by a calibrated pH meter (FE28-Standard, Mettler Toledo,
China). In the same supernatant filtrate, concentrations of soil Na, K,
Ca and Mg were determined by ICP-AES(Optima 2100DV, Pekin-Elmer, USA)
(Xin et al. , 2010). Soil Cl- was measured by
the silver nitrate titration method (Asakai, 2018).
To determine total nitrogen, total phosphorus and total potassium, we
weighed 0.25 g of soil, added 4 mL of aqua regia, digested at 180°C for
20 min, then added 2 mL perchloric acid, and digested at 280°C until the
brown smoke disappeared. Ultrapure water was used to make up the volume
to 100 mL, followed by filtration. The filtrates were measured by
ICP-AES (Optima 2100DV, Pekin Elmer, USA) (Semenkov & Koroleva, 2019).
Soil organic matter was measured using the potassium dichromate
volumetric method (Osman et al. , 2013). Available phosphorus was
determined by NaHCO3 extraction followed by the
molybdenum-antimony colorimetric method (Wang et al. , 2011b).
Available potassium was determined by flame photometry (AP1200, Aopu,
China) (Bilias & Barbayiannis, 2019).
2.4 Soil enzyme activities
Soil alkaline phosphatase was determined by a Soil Alkaline Phosphatase
(S-AKP) Assay Kit (Cat. No. BC0280, Solarbio, Beijing, China) by
measuring phenol produced during substrate hydrolysis (Ma et al. ,
2011). For soil catalase activity, we used a Soil Catalase (S-CAT) Assay
Kit (Cat. No. BC0105, Solarbio, Beijing, China) (Johnson & Temple,
1964). Soil urease activity was measured by a Soil Urease (S-UE) Assay
Kit (Cat. No. BC0120, Solarbio, Beijing, China). The indophenol blue
colorimetric method was used to measure the NH3-N
produced in urea hydrolysis by urease (Vlek et al. , 1980).
2.5 Microbial analyses
2.5.1 Soil DNA extraction
Soil DNA was extracted from 0.3 g of sieved (1 mm) soil using a Power
Soil DNA Isolation Kit (MO BIO Laboratories, Inc., Carlsbad, CA, USA).
The extracted genomic DNA was assessed by 1% w/w agarose gel
electrophoresis and stored at -80°C (Rodrigues et al. , 2013).
2.5.2 PCR amplification
PCR amplification of the V3-V4 region of bacterial 16S rDNA was
conducted using the universal primers 341F (5′-ACTCCTACGGGAGGCAGCAG-3′)
and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). PCR amplification of the fungal
ITS1-ITS2 region was performed using the universal primers ITS1
(5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2 (5′-TGCGTTCTTCATCGATGC-3′).
Amplification reactions were performed in 25 μL volume containing 12.5
μL 2xTaq Plus Master Mix, 5 μM of each primer, and 30 ng of template.
PCR was carried out under the following conditions: 94℃ for 5 min, 28
denaturation cycles (bacteria) or 34 denaturation cycles (fungi) at 94℃
for 30 s, annealing at 55℃ for 30 s, extension at 72℃ for 60 s,
extension at 72℃ for 7 minutes, and then cooling to 4°C.
2.5.3 MiSeq sequencing
PCR products were recovered by 2% w/w agarose gel electrophoresis,
purified using an Axy Prep DNA Gel Recovery Kit (AXYGEN), eluted by
Tris_HCl, and detected by 2% w/w agarose electrophoresis.
High-throughput sequencing was performed using Illumina MiSeq PE300
sequencing technology. QIIME (Quantitative Insights Into Microbial
Ecology) quality filters were used to filter the reads. The CD-HIT
pipeline was used for picking operational taxonomic units (OTUs) with
similarity of 97%.
Based on the 16S rDNA PCR amplification, a linear discriminant (LDA)
effect size (LEfSe) analysis was conducted to identify species with
significant differences in richness among treatment groups and to
construct cladograms (Segata et al. , 2011).
In order to estimate alpha diversity, the OTU table was rarified, and
three metrics were calculated: Chao 1 index to estimate the richness,
the observed OTUs, and Shannon index to estimate diversity
(Vishnivetskaya et al. , 2011).
2.6 Statistical analysis
Each type of soil was measured in three independent replicate samples.
The mean values and standard error of the means were calculated.
Statistical analyzes were performed using IBM SPSS Statistics 20.0 (IBM,
Armonk, New York, USA) and the mean differences were compared using
Duncan’s new multiple range test (p≤0.05). The software used to draw
figures was GraphPad Prism 8.0.1 and R package ggplot2 (version 3.2.0).
The Venn diagrams of the OTUs were generated using the R package venn
diagram (version 1.6.20). The PCA and redundancy analysis were created
using the R package vegan (version 2.5–5). The correlations among soil
physico-chemical and enzymatic properties were generated using the R
package corrplot (version 0.84).
3 RESULTS
3.1 Basic soil properties
3.1.1 Soil salinity and pH
Soil salinity decreased significantly in the following order:
CK>BS>RS. Compared with CK and BS, the
salinity of RS decreased by 87% and 76%, respectively (Figure 1a).
Soil pH was a little higher in RS than CK and BS (Figure 1b).
3.1.2 Concentrations of extractable soil elements
Concentrations of extractable Na, Mg,
K, Ca and Cl- all decreased in the order:
CK>BS>RS, and there were significant
differences between CK and RS (Figure 2). Compared with CK and BS, Na
concentration in RS decreased by 76% and 64%, respectively (Figure
2a). The concentration of Mg in soil was very low, only 0.027 g/kg in RS
(Figure 2b). The Cl- concentration in soil changed the
most in the process of phytoremediation, with CK being 9.6 times higher
than RS (Figure 2e).
3.1.3 Soil nitrogen, phosphorus, potassium and organic matter
Total nitrogen and organic matter in soil increased in the order of
CK<BS<RS (Table 1). Total phosphorus and available
phosphorus were significantly improved only in RS. Total potassium and
available potassium did not differ significantly among the soil samples.
3.1.4 Soil enzyme activities
The activity of soil alkaline phosphatase increased in the order:
CK=BS<RS, and was higher in RS by 85% and 74% compared with
CK and BS, respectively (Figure 3a). The urease activity in the soil
showed the same trend (Figure 3b).
Catalase activity did not differ
significantly among soils (Figure 3c).
3.2 Soil microorganisms
3.2.1 Analysis of soil microbial diversity
The sequencing coverage rate was greater than 0.986 (Table 2),
indicating that the sequencing information properly reflected a vast
majority of microbial diversity in soil. Bacterial Shannon and Chao1
indices were both in the order of CK<BS<RS, with
significant differences, indicating that Melia azedarach L.increased the richness and diversity of bacterial communities. There was
no significant difference in fungal Chao1 index, whereas the fungal
Shannon index was significantly lower in BS and RS compared with CK,
indicating that Melia azedarach L . enhanced fungal richness, but
had no significant effect on fungal diversity.
The bacterial OTU values in CK, BS and RS were 2242, 2636 and 3388,
respectively (Figure 4a). The fungal OTU values in CK, BS and RS were
1107, 782 and 910, respectively (Figure 4b). For both bacteria and
fungi, the OTU values were greater in RS than BS, indicating Melia
azedarach L. roots played an important role in enriching soil microbial
populations.
PCA (Principal Component Analysis) was performed at the OTU level. The
results showed discrete groupings of the three soil sample types,
indicating relatively large differences among them (Figure 5).
3.2.2 Analysis of microbial community structure
Bacterial community composition included 11 identified phyla, with
Proteobacteria, Actinobacteria and Bacteroidetes being the three
dominant phyla (Figure 6a). Proteobacteria was the most abundant phylum
in soil; the relative abundance in CK, BS and RS was 40-45%, 31-44%
and 40-46%, respectively. The relative abundance of Actinobacteria in
CK, BS and RS was 27-31%, 17-21% and 11-16 %, and that of
Bacteroidetes was 6.3-8.4%, 13-19% and 11-12%, respectively. The
proportion of other bacterial phyla was relatively low.
A total of nine fungal phyla were identified (Figure 6b). Ascomycota,
Basidiomycota and Glomeromycota were the three dominant fungal phyla.
The relative abundance of Ascomycota in CK, BS and RS was 27-37%,
82-87% and 44-69%, respectively. The relative abundance of
Basidiomycota was 3.6-12%, 3.2-5.0% and 23-35%, and that of
Glomeromycota was 9.5-12%, 0.09-0.15% and 0.01-0.28%, respectively.
The abundance of the three dominant fungal phyla differed widely among
the soils. Ascomycota had the highest abundance in BS, Basidiomycota had
the highest abundance in RS, and Glomeromycota were found mainly in CK.
The cladograms showed the taxa (highlighted by small circles) that
played an important role in the microbial community. The taxonomic tree
of bacteria (Figure 7a) showed that, at the class level, Acidimicrobiia,
Nitriliruptoria, Cytophagia, Longimicrobia were abundant in the bulk
soil, Chloroplast, S0134_terrestrial_group, Betaproteobacteria,
Deltaproteobacteria were abundant in the rhizosphere soil. At the order
level, Chromatiales was abundant in the bare soil, Acidimicrobiales,
Nitriliruptorales, Cytophagales, Longimicrobiales, Erythrobacteraceae
were riched in the bulk soil, Rhizobiales, Myxococcales, Chromatiales
were riched in the rhizosphere soil. At the family level, OM1_clade,
Nitriliruptoraceae, Longimicrobiaceae, Erythrobacteraceae were abundant
in the bulk soil. The taxonomic tree of fungi (Figure 7c) showed that at
the class level Rhizophlyctidomycetes was abundant in the rhizosphere
soil. At the order level, Microascales were abundant in the bulk soil,
Hypocreales, Agaricales, Rhizophlyctidales were abundant in the
rhizosphere soil. At the family level, Didymosphaeriaceae was abundant
in the bare soil, Chaetomiaceae were abundant in the bulk soil,
Rhizophlyctidaceae was abundant in the rhizosphere soil.
The LDA scores distribution histograms showed significant differences in
richness among the soils, with the length of the bars representing the
magnitude of the microbial influence. Regarding bacterial genera,Thiohalophilus was abundant in the bare soil, Cesiribacterwas abundant in the bulk soil (Figure 7b). At the level of fungal
genera, Malbranchea was abundant in the bulk soil, andRhizophlyctis was enriched in the rhizosphere soil (Figure 7d).
3.3 Association analysis between microorganisms and soil properties
Microbial data were combined with soil physico-chemical and enzymatic
properties to explore the correlations between the environmental factors
and microbial abundance and diversity. Salinity, Na, K, Ca and
Cl- showed significant negative correlations with
bacterial Chao1 index and Shannon index. Phosphorus, organic matter,
urease and total nitrogen were significantly and positively correlated
with bacterial Chao1 index and Shannon index (Figure 8).
The effects of soil environmental factors on microbial phyla were
analyzed by RDA (Figure 9). Total phosphorus and alkaline phosphatase in
soil had significant influence on bacterial diversity. Available
potassium and catalase had a positive correlation with Proteobacteria,
and Mg and Ca correlated positively with Actinomycetes. Total potassium
had a positive correlation with Bacteroidetes (Figure 9a).
The RDA analysis of fungi showed that Ca and Mg were closely related to
fungal diversity. Total potassium had a positive correlation with
Ascomycota, pH and total phosphorus correlated positively with
Basidiomycota, and Mg and Ca had a positive correlation with
Glomeromycota (Figure 9b).
4 DISCUSSION
Saline-alkali soils have poor productivity unless improved by
appropriate ameliorative measures (Singh et al. , 2016).
Phytoremediation has attracted increasing attention in amelioration of
saline-alkali soils because of its low economic cost and environmentally
friendly characteristics (Qadir et al. , 2003). In this study, the
positive effect of planting Melia azedarach L. on properties of
saline-alkali soil was obvious. Melia azedarach L. reduced soil
salinity and the content of extractable elements, increased soil total
nitrogen, total phosphorus, available phosphorus, organic matter and
enzyme activities, indicating it could improve the physical and chemical
properties of saline-alkali soils.
Soil salinity is an important factor restricting global sustainable
development, aggravating soil water and nutrient losses (Nouri et
al. , 2017). Excessive salinity reduces soil productivity, affects the
metabolism of soil organisms, interferes with ionic balance, and induces
osmotic stress in plants (Pan et al. , 2011; Yue et al. ,
2020). In the study presented here, soil salinity reduced the diversity
and abundance of bacteria (Figure 8); however, planted Melia
azedarach L. significantly reduced soil salinity, changing the soil
from highly saline to slightly saline (Figure 1a). However, as salinity
decreased, the soil pH showed a slight upward trend (Figure 1b), which
may be related to the litter of Melia azedarach L. being rich in
base cations.
Saline-alkali soils usually contain high concentrations of salt
elements. Excessive Na causes soil dispersion, plant toxicity, and may
cause mineral nutrition problems; other elements, such as K,Ca,Mg and
Cl- can also harm plants by reducing osmotic potential
of soil solution (Sparks, 1995). In the present study, planting ofMelia azedarach L. decreased Na, K, Ca, Mg and
Cl- concentrations in soil (Figure 2), showing this
plant species could remove excess elements to improve the properties of
saline-alkali soil.
Total nitrogen, total phosphorus, available phosphorus and organic
matter were highest in the rhizosphere soil of Melia azedarach L.and lowest in the bare soil (Table 1). These findings may be due to the
root exudates and litter of Melia azedarach L. being decomposed
by soil organisms, thereby increasing soil nutrients.
Enzymes regulate many soil biological processes and are secreted by soil
microorganisms, plants and animals (Marx et al. , 2001).
Phosphatase activity is an indicator of soil phosphorus cycling; it can
catalyze the hydrolysis of the ester-phosphate bond and release
phosphate (Nannipieri et al. , 2011). Soil urease activity is a
factor influencing soil nitrogen content (Albiach et al. , 2000).
The activity of soil catalase is related to soil respiration intensity
and the activity of soil microbial communities (Cheng et al. ,
2013). In the study presented here, Melia azedarach L. increased
the activities of alkaline phosphatase and urease in saline-alkali soil
(Figure 3a, Figure 3b), indicating the capacity of this plant species to
promote soil phosphorus and nitrogen cycling. Catalase activity was
higher in RS than BS (Figure 3c), indicating that Melia azedarach
L. root system had positive effect on the activity of microorganisms.
Soil microorganisms play an important role in maintaining soil ecosystem
functions, including organic matter decomposition, nutrient cycling,
bioremediation, soil organic matter stabilization, and soil aggregate
formation (Dangi et al. , 2018). The MiSeq sequencing results
showed that planting of Melia azedarach L. increased the
abundance and diversity of bacteria, but reduced the abundance and
diversity of fungi (Table 2), which may be related to a decrease in
salinity. Other studies have shown that low-salt soils have lower fungal
biomass than high-salt soils (Muhammad et al. , 2006).
Proteobacteria is the largest phylum of soil bacteria, including many
bacterial taxa with agricultural importance, e.g. those involved in
N2 fixation and soil nitrogen cycle (Spain et
al. , 2009). In the present study, the abundance of Proteobacteria was
higher in the Melia azedarach L. rhizosphere than bulk and bare
soil, indicating that the planting of Melia azedarach L. can
improve the availability of nitrogen. In addition to a role in N
availability, Proteobacteria can serve as biocontrol agents in the
soil-plant ecosystem (Lueders et al. , 2006).
Ascomycota play an important role in most terrestrial ecosystems.
Ascomycota can decompose organic matter, thus playing an important role
in nutrient cycling. The fruiting bodies of Ascomycota provide food for
many animals, and many Ascomycota also form symbiotic relationships with
other organisms, including plants. In this study, Ascomycota was the
dominant fungal phylum, which was most abundant in the bulk soil,
whereas one of Acomycota genera (Rhizophlyctis ) was significantly
enriched in the rhizosphere soil. Other studies have shown thatRhizophlyctis may play an important role in decomposition of
organic matter in many soil-based ecosystems (Weber & Webster, 2000).
Microbial diversity is affected by biotic as well as abiotic factors
(Singh et al. , 2009). High salinity, Na, K, Ca and
Cl- concentrations reduced the diversity and abundance
of bacteria, whereas increased phosphorus, organic matter, urease and
total nitrogen were associated with increased diversity and abundance of
bacteria (Figure 8). The results of RDA showed that total phosphorus and
alkaline phosphatase were the most important factors influencing
diversity of bacterial communities in soil, whereas Ca and Mg were
related closely to the fungal diversity (Figure 9). Planting Melia
azedarach L. improved the properties of the saline-alkali soil, thereby
increasing the diversity of the soil microbial communities.
5 CONCLUSIONS
This study explored a phytoremediation potential of Melia
azedarach L. to improve saline-alkali soil. Melia azedarach L.not only reduced soil salinity and the content of extractable elements,
but also increased (i) nitrogen, phosphorus and organic matter content
as well as enzyme activities, and (ii) the diversity and abundance of
soil microbial communities to improve the properties of coastal
saline-alkali soil. This study provided a scientific basis for (i) usingMelia azedarach L. in remediation of coastal saline-alkali soils
and (ii) the understanding of the underlying ameliorative mechanisms.
ACKNOWLEDGMENTS
This work was financially supported by Forestry Science and Technology
Innovation and Extension Project of Jiangsu Province (No.
LYKJ[2019]07), the Natural Science Foundation of Jiangsu Province of
China (BK20181165), the 5th Scientific Research Project of “333
High-level Talents Training Project” of Jiangsu Province (BRA2020128),
the National Key Research and Development Program of China
(2016YFC0501207), the Jiangsu Agricultural Science and Technology
Independent Innovation Fund Project [CX(18)2013], the National Key
Project of Scientific and Technical Supporting Programs funded by the
Ministry of Science & Technology of Jiangsu Province (BE2018387 and
BE2017310-2), and the Fundamental Research Funds for the Central
Universities (KYYJ201902, KYZ201623, YZ2016-1 and KYYJ201703).
CONFLICT OF INTEREST
There are no competing financial interests associated with the
publication of this article.
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