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Article

Community Composition Specificities of Cyanobacteria in Paddy Soil under Different Ecological Conditions

by
Jian Song
1,
Xu He
1,
Shuwen Wang
1,
Xue Yang
1,
Lei Wu
1,
Siyuan Li
1,
Dongchao Wang
2,
Meiying Yang
1,* and
Zhihai Wu
2,*
1
College of Life Sciences, Jilin Agricultural University, Changchun 130118, China
2
College of Agronomy, Jilin Agricultural University, National Characteristic Station for Crop Variety Approval, Changchun 130118, China
*
Authors to whom correspondence should be addressed.
Agronomy 2022, 12(12), 3090; https://doi.org/10.3390/agronomy12123090
Submission received: 10 November 2022 / Revised: 3 December 2022 / Accepted: 5 December 2022 / Published: 6 December 2022
(This article belongs to the Special Issue Recognition and Utilization of Natural Genetic Resources for Advances in Plant Biology through Genomics and Biotechnology)
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Abstract

:
In order to explore the distribution of cyanobacteria in paddy soil under different ecological conditions, the composition, diversity, and environmental drivers of soil cyanobacteria communities in rice fields from six regions of Jilin Province (China) were investigated. The results showed that the 16S amplicon high-throughput sequence detected the existence of cyanobacteria of 16 phyla, 33 orders, 60 families, and 113 genera in the soil of rice fields in Jilin Province. The dominant cyanobacteria populations in Jilin Province paddy soils comprised Cyanobium_PCC-6307, Synechocystis_PCC-6803, Planktothrix_NIVA-CYA_15, and Nodosilinea_PCC-7104. Each soil sample included a significant proportion of nitrogen-fixing filamentous cyanobacteria Anabaena and Nostoc according to microscopic analysis. The structural properties and diversity of cyanobacteria communities differed by geography, with soil pH and SOC being the main environmental drivers of cyanobacteria community structure. The alkaline soils S1, S2, and S5 displayed greater diversity than the acidic soils S3, S4, and S6, with S5 displaying the greatest cyanobacteria diversity. This research has crucial implications for developing and utilizing local cyanobacteria resources.

1. Introduction

Soil microbes have important roles in soil ecosystems, such as nutrient cycling, energy metabolism, and organic matter decomposition [1]. Soil microorganisms are an important indicator for evaluating soil quality; soil quality is positively correlated with the quantity and diversity of soil microorganisms [2]. Cyanobacteria are widely regarded as important soil microorganisms for agricultural production because they can perform a variety of biological roles, including photosynthesis [3], solubilizing phosphate [4], nitrogen fixation [5], etc.
Blue-green algae are one of the world’s oldest living things. They can thrive in various environments, including different water bodies, soils, and even rock surfaces, as well as environmental extremes, such as high and low temperatures, salt lakes, deserts, and glaciers [6]. The current reports on cyanobacteria community structure primarily focus on tropical locations or areas with little anthropogenic influence. According to a study on the diversity of cyanobacteria in the southeast Tengger Desert, the composition of cyanobacteria in different types of biological crusts varies, and the seasonal dynamics influence the composition, dominant groups, and core groups of cyanobacteria communities [7]. Borchhardt et al. [8] discovered great species richness in Antarctic crustal communities, with varying species compositions at different sampling sites in their studies on algal diversity in the Adelie and King George Islands, Antarctica. Machado et al. [9] investigated cyanobacteria biocrust’s composition, abundance, and environmental drivers in Caatinga and Pampa, Brazil. They discovered that soil temperature and pH were the key factors explaining the findings. Moreover, Caatinga locations with more arid environments featured more N-fixing cyanobacteria. In contrast, Pampa areas with higher rainfall regimes had a higher abundance of biocrust-forming bacteria such as Microcoleus and Leptolyngbya. It has also been studied in lakes and rice wetlands. In a study of cyanobacteria diversity in a highland reservoir in Guizhou, China, it was found that the reservoir was dominated by Pseudanabaena, Limnothrix, Merismopedia, Chroococcus, and Cylindrospermopsis raciborskii. Cyanobacteria diversity in reservoirs changes with the seasons. Temperature, light, and nutrients were the main influences on cyanobacteria diversity in the reservoir [10]. Gu et al. [11] studied the composition of rice cyanobacteria communities in Ningxia, China, and found that the structural composition of paddy cyanobacterial communities was dominated by the filamentous Chlorella subclass Oscillatoriophycideae, and that pH was the main environmental factor driving the distribution of cyanobacteria in the water column. To summarize, all the studied locations exhibit similar cyanobacteria community structures, although there are considerable variances in ecological diversity.
Cyanobacteria are valued biological resources in agriculture, ecosystems, and environmental sustainability [12]. Gram-negative cyanobacteria are autotrophic prokaryotes that perform oxygenic photosynthesis, making them a promising renewable biotic resource for producing green fuels and chemicals as a replacement for the traditional biomass-based “microbial cell factory” [13]. Diazotrophic cyanobacteria are thought to be crucial in the modern nitrogen cycle [14]. Cyanobacteria in cryptogamic covers, e.g., Microcoleus, Leptolyngbya, and Pseudanabaenaceaeare have been identified as key actors, accounting for about half of the total biological nitrogen fixation on land [15]. Cyanobacteria biomass is an efficient bio-fertilizer source for improving the physicochemical properties of soil, such as water-retention ability and mineral nutrient status in degraded lands. Cyanobacteria can supply 20–30 kg N ha−1 and organic matter to the soil, reducing the need for chemical nitrogen fertilizers. Because cyanobacteria do not compete for carbon or energy with crops or heterotrophic soil microbiota, numerous nitrogen-fixing cyanobacteria have been utilized as biofertilizers [7]. Several cyanobacteria species, such as Anabaena variabilis, Nostoc muscorum, Aulosira fertissima, and Tolypothrix tenuis, were discovered to be food biofertilizers. Cyanobacteria can also help to improve the soil environment by increasing soil particle aggregation and water retention capacity. By releasing organic acids, Westiellopsis prolifica and Anabaena variabilis can boost phosphorus efficacy [16]. Cyanobacteria provide extracellular plant growth-promoting substances such as hormones, vitamins, and amino acids [12].
Cyanobacteria have an impact on the growth of most crops, particularly rice. Because of the unique ecological environment of paddy wetlands, cyanobacteria can be found in enormous numbers. Thus, Phormidium, Leptolyngbya, Nostoc, Oscillatoria, and Anabaena, all well-known settlers in rice fields, have been discovered [17]. Among them, Anabaena and Nostoc are usually regarded as biological nitrogen-fixing bacteria that increase the nitrogen content and nitrogenase activity in rice fields [18]. Cyanobacteria have been found in studies to enhance nitrogen content and nitrogenase activity in rice fields [19], allowing the rice to satisfy 30%~50% of its urea nitrogen requirement [20]. It was reported as early as 1984 that the presence of cyanobacteria maintained the fertility of Indian rice fields [21]. Despite growing interest in the cyanobacteria community, there are still some knowledge gaps, particularly regarding paddy field wetlands under the climate conditions in China’s northeast inland, where research is still limited. As a result, we isolated and identified soil cyanobacteria from six different areas of rice fields in Jilin Province (China) using Illumina MiSeq sequence technology and morphological observations. We investigated each soil’s structural composition, diversity, and environmental drivers of cyanobacteria communities. This research is significant for clarifying the distribution of soil cyanobacteria in diverse ecological locations, searching for nitrogen-fixing cyanobacteria strains, and developing and utilizing local cyanobacteria resources.

2. Materials and Methods

2.1. Study Site and Soil Collection

The test soils were collected from six distinct locations in Jilin Province (Figure 1), S1–S6. This test soil sample was obtained in July 2021. To collect rice inter-root soil (0–20 cm), a five-point sampling approach was utilized, with five subsamples combined thoroughly to make a single replicate and four sets of replicates set up for each sampling site (n = 24). The root shaking method was used to collect inter-root soil samples. After shaking off most of the clay adhering to the roots, the roots with soil were cut off using scissors and placed in sterile tubes with sterile PBS, and the attached inter-root soil was shaken off. Soils were sieved (<2 mm) and preserved in three portions: air-dried, at 4 °C, and at −80 °C for soil physicochemical analysis, soil cyanobacteria observation, and for molecular analysis, respectively. The data on temperature and rainfall climatic conditions in 2021 for each region are provided by the Jilin Provincial meteorological bureau (Table 1). Fertilizer management at each sampling site was managed according to the traditional fertilizer application (basal fertilizer: tiller fertilizer: cone fertilizer, 6:3:1). Within 3–5 days after transplanting, cyhalothrin emulsifiable concentrates and fertilizers were applied together to control pests. From 10–20 June, chlorofluorobenzamide spray was used to control Chilo suppressalis. At the end of July, Daowenling emulsifiable concentrates were sprayed to control rice blast. “Daowenling” is also known as “Isoprothiolane”, whose molecular formula is C12H18O4S2 (Di-isopropyl 1,3-dithiolan-2-vinylmalonate) (Hubei xin bonus chemical Co., Wuhan, China).

2.2. Analyses of Soil Variables

The soils were air-dried and passed through 1.00 mm and 0.15 mm sieves to be tested. Soil samples were immersed in deionized water (1:5 v/v) and a pH meter (Thermo Orion 720A, USA) was used to determine the soil pH [22]. Total nitrogen (TN) was determined using concentrated sulfuric acid decoction and Kjeldahl nitrogen determination, and its content was calculated [23]. Nitrate nitrogen (NO3−-N) was determined using the phenol-disulfonic acid colorimetric method [24]. Ammonium nitrogen (NH4+-N) concentration was determined using the indophenol blue colorimetric method [25]. Total organic carbon (TOC) was determined using the external heating method with potassium dichromate [26]. The available phosphorus (AP) concentration was determined by Sodium bicarbonate extraction— the molybdenum antimony anti-colorimetric method [27]. The available potassium (AK) concentration was determined by ammonium acetate leaching—the flame photometric method [28].

2.3. Morphological Evaluation of Cyanobacteria

Soil samples were enriched with BG-11 (Table S1) medium for 15 d at 25 °C, 2000 lux light intensity, and 14 h:10 h light/dark photoperiod. The algae were isolated using the BG11 solid medium plate scribe method. Morphological observations made with a microscope (OLYMPUS CX23, Beijing, China) and specific steps for algae identification follow the literature [29,30].

2.4. DNA Extraction and Illumina MiSeq Sequencing

Total genomic soil DNA was extracted from 0.25 g soil samples (dry weight equivalent) by using a Power Soil® DNA Isolation Kit (Qiagen, Hilden, Germany) as per the manufacturer’s instructions. The V3-V4 region of the 16S rRNA gene was amplified by PCR using cyanobacteria universal primers cya359 and 781a/b (Table S2) [31]. The PCR products were extracted from 2% agarose gels and purified using the DNA Gel Extraction Kit (Axygen, Hangzhou, China). The purified amplification products were combined in equimolar amounts and sequenced on the Illumina Novaseq sequence platform per MajorBioBio-pHarm Technology Co.’s standard methodology.

2.5. Data Analysis Pipeline and Operational Taxonomic Unit Taxonomic Assignment

Trimmomatic [32] (v0.33) software was used to filter raw readings acquired from sequencing. Cutadapt [33] (v1.9.1) software performed primer sequence identification and removal to obtain clean reads that do not contain primer sequences. The clean reads of each sample were spliced by overlap using Usearch [34] (v10) software, and the spliced data were sorted into lengths depending on the length range of the distinct sections, with only sequences between 251-473 bp kept. The chimeric sequences were detected and deleted using UCHIME [35] (v4.2) software to produce the final effective reads. Reads were clustered, and operational taxonomic units (OTUs) were recovered with a 97.0% similarity level using Usearch [32] (v10.0) software. Taxonomic annotation of the feature sequences using a simple Bayesian classifier with SILVA [36] (Release132, http://www.arb-silva.de, accessed on 1 March 2021) as the reference database yields taxonomic information on the species corresponding to each feature. Finally, the number of all sequences corresponding to each OTU is counted, and the obtained results are recorded in a table file to obtain each genus and its corresponding number of sequences. All sequence datasets were submitted to NCBI as part of the “Rice cyanobacteria diversity raw sequence reads” project (NCBI submission number: SUB11716251).

2.6. Statistical Analyses

To undertake statistical analysis, R version 4.0.2 (R Core Team, 2020) and Primer 6 software version 6.1.11 (Primer-e Ltd., Plymouth, UK) were used. Microbial α-diversity incorporates several components, including evenness, phylogenetic diversity, and Shannon variety, whereas species richness shows diversity directly and is often employed to define the microbial alpha diversity. Alpha diversity is analyzed using the QIIME2 (https://qiime2.org/, (accessed on 5 March 2021)) program. OTU phylogenetic tree analyses were carried out using a Galaxy-based pipeline (http://mem.rcees.ac.cn:8080, (accessed on 5 March 2021)) with PyNAST alignment and FastTree, and the β-diversity (weighted UniFrac dissimilarity) of the bacterial community was calculated [37]. To explain the correlation of environmental data with the distribution of OTUs, the R packages “vegan”, “ggplot2”, and “gridBase” (R Core Team, 2020) were used. The spatial distribution of cyanobacteria colonies was visualized using redundancy analysis (RDA) as a constrained ranking method.

3. Results

3.1. Analysis of Climatic Conditions and Physicochemical Properties of Soil Sample Sampling Sites

The average temperature ranged from 11.1 to 12.5 °C at six separate sites in Jilin province, with S1 having a high average temperature of 12.5 °C. S6 had a low average temperature of 11.1 °C, and the average temperature decreases gradually from S1 to S6. On the contrary, average precipitation increases gradually from S1 to S6. S5 measures the highest at 301.6 mm, whereas S1 is lower, at 200.7 mm (Table 1).
The basic physicochemical parameters of soil samples from each site are displayed in Table 2. We can see that the soil nutrient level varies substantially from S1 to S6. The organic carbon (TOC) content of soil varied from 5.31 to 15.19 g·kg−1. S1 and S5 had significantly greater levels than the other locations, with 15.19 g·kg−1 and 15.07 g·kg−1, respectively. S3 was 5.31 g·kg−1, which was relatively low. The total nitrogen (TN) levels ranged from 1.96 to 3.32 g·kg−1, with S5 being the highest and S3 being the lowest. The ammoniacal nitrogen (NH4+-N) content of S5 was significantly higher than the other sites, reaching 139.65 mg·kg−1. S1 had a lower ammoniacal nitrogen content of 17.89 mg·kg−1. Soil available phosphorus (AP) and available potassium (AK) levels were highest for S5 and lowest for S3. The adequate phosphorus and effective potassium were 22.84 mg·kg−1 and 306.5 mg·kg−1 in S5, and 13.74 mg·kg−1 and 183.8 mg·kg−1 in S3, respectively. Among all sites, S1, S2, and S5 are characterized by alkaline soils, and S3, S4, and S6 by acidic soils. The soil pH of S1 was the highest, at 8.01. The pH of S6 was the lowest, at 6.05.

3.2. Morphological Observation of Soil Cyanobacteria

Soil cyanobacteria play a vital role in soil ecology. Many filamentous cyanobacteria were observed in rice in the inter-rhizosphere soil. A total of 13 filamentous cyanobacteria species were discovered (Figure 2), including Leptolyngby, Oscillatoria, Lyngbya, Phormidium, Heteroleibl, Porphyrosip, and Microchaet. The cyanobacteria Anabaena and Nostoc with heteromorphic cells were also discovered. Anabaena and Nostoc are usually found in S1 and S5 locations. We isolated two nitrogen-fixing cyanobacterial strains and constructed a phylogenetic tree (Figure S1).

3.3. Cyanobacteria Communities Composition and Structure

A total of 1,920,722 reads were obtained, and a total of 1,913,320 clean reads with an average length of 400–420 bp were generated after double-ended reads quality checks and splicing for future analysis. The sequences were grouped into OTUS for species classification, yielding a total of 490 OTUS, and the abundance of each OTUS in various samples was counted. When sequenced sequences were greater than 30,000, the dilution curves of rice soil samples from different regions (Figure 3) showed no significant increase in the number of OTUs at a 97% similarity level (α = 0.03), indicating that the sequencing results were plausible.
A total of 16 classes, 33 orders, 60 families, and 113 genera of cyanobacteria were detected. A total of 113 cyanobacteria genera were detected at the taxonomic level of the genus. The dominant cyanobacteria species in the inter-rhizosphere soil of rice in Jilin Province were Cyanobium_PCC-6307 (3.8–54%), Synechocystis_PCC-6803 (0.17–9.9%), Planktothrix_NIVA-CYA_15 (0.03–5.3%), and Nodosilinea_PCC-7104 (1.1–9.1%) (Figure 4). However, there were considerable variances between the inter-rhizosphere compositions. Rice soil cyanobacteria colonies were found in various regions.
The results of an LDA analysis (Figure 5) showed that at the taxonomic level of genera, significant variation was observed in different geographical areas for Nodosilinea, Letolymgbya, Cyanobium, Synechocystis, and Leptolyngbya. The significantly different species in S1 was Nodosilinea, in S3 was Cyanobium, in S4 was Limnothrix, in S5 was Leptolyngbya and in S6 was Synechocystis. Cyanobium_PCC-6307 was widely dispersed in S3, accounting for 51.8% of the total, although it only made up 3.1% of the total in S1. Cyanobium_PCC-6307 showed a significant negative correlation with soil nutrient content (p < 0.01). Nodosilinea_PCC-7104 accounted for 8.8% of the species in S1 but only 1.2% in S6. Nodosilinea_PCC-7104 showed a significant positive correlation with PH and SOC (p < 0.01) (Figure 6). The taxonomic makeup of cyanobacteria communities in rice inter-rhizosphere soils revealed that single cells or communities were the most prevalent component, accounting for 24% of the total (RA). Filamentous cyanobacteria represented 9.36% of RA, with heterocytic cyanobacteria making up 4.8% of RA, and the soil contained many uncultured cyanobacteria taxa (Table S3).

3.4. Diversity Analysis of Soil Cyanobacteria Community

The Chao1 and ACE indices indicate an abundance of cyanobacteria in the inter-rhizosphere soil of rice (Figure 7). Soil cyanobacteria concentration was higher at S4 and S5 than at S1, S2, S3, and S6, with the lowest concentration in S3. The Shannon and Simpson indices revealed the microbial diversity of rice inter-rhizospheric soil cyanobacteria. Soil cyanobacteria diversity was higher in S1 and S5 than in S2, S3, S4, and S6, with S3 having the lowest cyanobacteria diversity. S5 has high cyanobacterial diversity and species richness when taken as a whole. S3 has low cyanobacterial diversity and species richness.

3.5. Correlation between Operational Taxonomic Units and Environmental Variables

Environmental factors pH, AP, AK, TN, and SOC were chosen as predictor variables. Predictor variables were used for RDA analysis. The results of the RDA analysis revealed that the first two axes explained 54% of the community variation. The first axis divided the differences in community composition between areas S1, S5, and various additional places (Figure 8). Soil organic carbon (p < 0.05), pH (p < 0.05), total nitrogen (p < 0.05), and available phosphorus (p < 0.05) were all strongly correlated with the bacterial community structure. With a correlation coefficient of 0.8948, pH was probably the most dominant soil property (Table S4). The extent of each environmental factor’s effect was in the order of pH > organic carbon > total nitrogen > adequate potassium.

4. Discussion

Better knowledge of soil cyanobacteria community ecology and diversity is essential for a broader understanding of their roles in terrestrial ecosystems. There are many microalgae, including prokaryotic cyanobacteria, eukaryotic green algae, and diatoms [38], which can survive in various environments. Jilin Province, in northeastern China, in the eastern part of the Eurasian continent, has a temperate monsoon climate with cool summers, cold winters, and simultaneous rain and heat. The rice cultivation area and total production comprise nearly 30–40% of the national grain area and total production, respectively. In this study, we isolated and identified soil samples of cyanobacteria from six different regions in Jilin Province, using high-throughput sequencing of 16S amplification, and discovered that cyanobacteria were widely spread in paddy soils. The taxonomic composition of cyanobacteria assemblages in rice soil biota in the different regions was significantly varied, and various locations in each biota had varied assemblages. These discrepancies were influenced considerably by the soil and climate variables investigated, particularly SOC and pH.

4.1. Composition of Cyanobacterial Communities in the Inter-Rhizosphere Soil of Rice

Fertilizers are being over-applied on rice fields in order to meet the global food demand. These actions impact both the soil and the soil microbes. The cyanobacteria are expected to address this challenging problem. Because of their ability to perform biological nitrogen fixation and photosynthesis, cyanobacteria are considered natural biofertilizers. Given that the structural properties and diversity of cyanobacteria communities vary by location, there is an urgent need to investigate the composition, diversity, and environmental causes of local cyanobacteria communities.
Amplification sequencing allowed us to acquire a wider variety compared to morphological assessment. Nonetheless, microscopy revealed a plethora of filamentous cyanobacteria. The current study found a significant proportion of the filamentous cyanobacteria Planktothrix, Anabaena, Leptolyngbya, and Nostoc in each soil sample. In rice wetlands, non-heterotrophic species of cyanobacteria may become dominant when fertilizers are applied and heterotrophic strains of bacteria are suppressed [39]. In the present study, several nitrogen-fixing species, including Anabaena, Gloeocapsa, and Nostoc, were found in the farmland, along with more non-nitrogen-fixing species such as Lyngbya, Microcystis, and Oscillatoria. it is hypothesized that the occurrence of nitrogen-fixing species in rice fields may be an indication of nitrogen deficiency despite regular fertilizer application.

4.2. Influence of Climate on Cyanobacteria Community

Nitrogen is the most critical limiting nutrient for rice growth in paddy wetlands [40]. The nitrogen requirements of rice have been met through the use of chemical fertilizers. Algal biofertilizer is currently used as an alternative to fertilizer because it increases rice yields [41] and provides greater effective N content [42]. Previous studies found that nitrogen-fixing cyanobacteria improved soil quality by improving soil particle aggregation, water retention capacity, phosphorus effectiveness, and the quantity of microbiotas [41]. Cyanobacteria biofertilizers are ecologically benign and cost-effective for farmland. In this regard, the nitrogen-fixing cyanobacteria examined in this study are promising candidates for biofertilizer synthesis.
Moisture (humidity) has been found to play a very significant role in the distribution and diversity of soil algae [43]. Compared to other agricultural fields, the biomass dry weight of nitrogen-fixing cyanobacteria in rice fields ranged from a few kilograms to several hundred kilograms per hectare [44], and rice fields with medium or high moisture levels had higher algal species diversity [45]. There were substantial changes in cyanobacteria distribution due to rainfall in this study, and the two locations of S4 and S5, which received comparatively abundant rainfall compared to other areas, had higher cyanobacteria species richness than S1, S2, S3, and S6. Significantly different species, such as Letolymgbya, Synechocystis, and planktothrix, were positively correlated with precipitation in the S1 and S2 areas. This is in agreement with previous studies [46]. Rice cyanobacteria had higher diversity in areas with more precipitation.
However, it has also been demonstrated that soil temperature is the primary driver of the apparent differences in the taxonomic composition of the cyanobacteria communities in Caatinga and Pampa [9]. The S6 region in this study received higher precipitation, but the temperature was lower. The low temperature could explain why this area has lower cyanobacteria species richness and variety than others [47]. Changes in temperature and precipitation can modify the composition, dominant taxa, and core taxa of cyanobacteria communities in the substratum, and wet and dry treatments can produce variances in the abundance of cyanobacteria diversity [48]. This suggests that seasonal variations can significantly impact the structural properties of cyanobacteria communities.

4.3. Effects of Soil Properties on Cyanobacteria Community

Soil environment significantly influences the structure and diversity of algal communities [45]. Since many factors, including climate change, impact the soil physicochemical properties of paddy wetlands, intensive human activities such as tillage, fertilization, spraying of pesticides and herbicides, etc., have a greater impact on soil physicochemical properties, and differences in management practices in different rice areas alter the diversity of soil algae [49]. Our findings revealed significant disparities in the soil properties of paddy fields across Jilin Province, with higher nutrient concentrations such as N, P, K, and SOC in alkaline soils than in areas with acidic soils. Prasanna et al. [50] found that the optimal growth pH for most cyanobacteria is neutral. However, Wang et al. [51] revealed that soil pH and SOC are the most critical parameters affecting the inter-root bacterial community of maize. Soil pH affected Cyanobium_PCC-6307 and Nodosilinea_PCC-7104. Cyanobium_PCC-6307 was found extensively in acidic soils. Nodosilinea_PCC-7104 was suitable for alkaline soils. TN has also been identified as the main driver of microbial community structure [52]. In this study, we also discovered that, in addition to soil SOC and pH, TN was also the primary environmental factor influencing cyanobacteria diversity. Regular application of various fertilizers to increase productivity leads to the acidification of the soil environment. This may be why pH and TN are the main factors affecting cyanobacterial communities. This may also be the reason why cyanobacterial diversity is higher in the alkaline areas S1, S5 and S6 than in soused areas, which is why we observed a lot of Nostoc and Anabaena in rice with a higher distribution in alkaline areas. In summary, the combination of pH, SOC, and TN, influences cyanobacteria in diverse locations of Jilin Province, resulting in a locally distinct soil cyanobacteria community structure.

5. Conclusions

In this study, we investigated the structural composition, diversity, and environmental drivers of soil cyanobacteria communities in rice fields in six regions of Jilin Province. The results revealed regional differences in cyanobacteria communities’ structural characteristics and diversity. Cyanobacteria are greatly influenced by soil physicochemical properties, with pH, SOC, and TN being the main environmental drivers of cyanobacteria community structure. This study also isolated nitrogen-fixing strains of cyanobacteria, which can be used as raw materials for biofertilizers. In this paper, we emphasized the importance of soil and climate conditions in the composition and diversity of cyanobacteria biomes. This information can provide a basis for the conservation efforts of cyanobacteria communities.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy12123090/s1. Table S1. BG11 medium formulation; Table S2. Primer sequences and target sites; Table S3. Relative abundance of soil cyanobacteria in different areas of Jilin Province; Table S4. Significance of environmental variables in explaining the differences of cyanobacteria; Figure S1. Phylogenetic evolutionary tree of two isolated cyanobacterial strains.

Author Contributions

M.Y. and Z.W. designed and supervised the project; J.S., X.H. and S.W. analyzed the data and wrote the manuscript; X.Y., D.W., L.W. and S.L. participated in the material preparation. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the following funding sources: Jilin science and technology development plan project (2020040316SF) and the “Thirteenth Five-Year Plan” science and technology project of the Education Department of Jilin Province (JJKH20200335KJ).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data described in this study are available on request from the corresponding author. The data is not publicly available due to the involvement of other unpublished papers.

Conflicts of Interest

The authors declare no conflict of interest. The funders played no part in the study’s design, data collection, analyses, or interpretation, writing of the manuscript, or decision to publish the results.

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Agronomy 12 03090 g001 550
Figure 1. Map depicting the location of the sampling sites in Jilin Province. (a) Location of Jilin Province in China (b) Location of 6 sampling points in Jilin Province.
Figure 1. Map depicting the location of the sampling sites in Jilin Province. (a) Location of Jilin Province in China (b) Location of 6 sampling points in Jilin Province.
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Figure 2. Cyanobacteria were observed in rice rhizosphere soil samples (Bars = 10 µm). (a) Heteroleibleibleinia (S6), (b) Leptolyngbya gelatinosa (S6), (c) Porphyrosiphon luteus (S5), (d) Porphyrosiphon ceylanicus (S5), (e) Leptolyngbya foveolara (S4), (f) Lyngbya circumcreta (S1), (g) Nostoc Kihlmani (S1), (h) Microchaete tenera (S3), (i) Phormidium irriguum (S2), (j) Oscillatoria amoena (S2), (k) Nostoc muscorum (S1), (l) Anabaena constricta (S1).
Figure 2. Cyanobacteria were observed in rice rhizosphere soil samples (Bars = 10 µm). (a) Heteroleibleibleinia (S6), (b) Leptolyngbya gelatinosa (S6), (c) Porphyrosiphon luteus (S5), (d) Porphyrosiphon ceylanicus (S5), (e) Leptolyngbya foveolara (S4), (f) Lyngbya circumcreta (S1), (g) Nostoc Kihlmani (S1), (h) Microchaete tenera (S3), (i) Phormidium irriguum (S2), (j) Oscillatoria amoena (S2), (k) Nostoc muscorum (S1), (l) Anabaena constricta (S1).
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Figure 3. Dilution curve of samples at 97% similar level.
Figure 3. Dilution curve of samples at 97% similar level.
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Figure 4. Relative abundance of soil cyanobacteria in different areas of Jilin Province.
Figure 4. Relative abundance of soil cyanobacteria in different areas of Jilin Province.
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Figure 5. Histogram of the linear discriminant analysis scores of soil bacterial community at genus level. NOTE: p < 0.05, LDA score 4.0.
Figure 5. Histogram of the linear discriminant analysis scores of soil bacterial community at genus level. NOTE: p < 0.05, LDA score 4.0.
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Figure 6. Correlation heatmap between the cyanobacterial genus and soil nutrients Note: * (p < 0.05) ** (p < 0.01).
Figure 6. Correlation heatmap between the cyanobacterial genus and soil nutrients Note: * (p < 0.05) ** (p < 0.01).
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Figure 7. Diversity index of cyanobacteria communities in paddy soil in different regions. NOTE: (A) Shannon index; (B) Simpson index; (C) Chao1 index; (D) ACE index. Different letters indicate significant differences at p < 0.05.
Figure 7. Diversity index of cyanobacteria communities in paddy soil in different regions. NOTE: (A) Shannon index; (B) Simpson index; (C) Chao1 index; (D) ACE index. Different letters indicate significant differences at p < 0.05.
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Figure 8. Redundancy analysis (RDA) relating environmental variables with cyanobacteria diversity.
Figure 8. Redundancy analysis (RDA) relating environmental variables with cyanobacteria diversity.
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Table
Table 1. Site description of study sites in Jilin Province.
Table 1. Site description of study sites in Jilin Province.
Sample SitesGPS CoordinatesEcoregionAverage Precipitation (mm)Average Temperature (°C)
S145°40′ N, 122°88′ EArid plains200.7 d12.5 a
S245°03′ N, 124°96′ EArid plains106.1 f12.2 b
S343°80′ N, 125°41′ EHumid plains199.5 e12.1 b
S443°74′ N, 125°89′ EHilly and semi-mountainous287.5 b11.6 c
S542°42′ N, 125°59′ EHilly and semi-mountainous301.6 a11.3 d
S642°05′ N, 125°75′ EHilly and semi-mountainous236.4 c11.1 e
Different letters indicate significant differences at p < 0.05.
Table
Table 2. Physicochemical properties of the soil at the sampling point.
Table 2. Physicochemical properties of the soil at the sampling point.
Sample SitesSOC
(g·kg−1)		TN
(g·kg−1)		AN
(mg·kg−1)		AP
(mg·kg−1)		AK
(mg·kg−1)		pH
S115.19 ± 0.06 a2.16 ± 0.03 d17.89 ± 0.00 e25.01 ± 1.03 a202.50 ± 1.70 c8.01 ± 0.04 a
S210.80 ± 0.56 d2.63 ± 0.04 c22.68 ± 0.32 d13.88 ± 0.25 c233.20 ± 1.10 b7.35 ± 0.01 c
S35.31 ± 1.04 e1.96 ± 0.01 e44.01 ± 0.04 b14.43 ± 0.13 c201.10 ± 1.10 c6.65 ± 0.03 d
S412.02 ± 0.12 c2.63 ± 0.06 c24.78 ± 1.35 d13.74 ± 0.00 c183.80 ± 3.40 d6.49 ± 0.03 e
S515.07 ± 0.23 a3.32 ± 0.06 a139.65 ± 1.71 a22.84 ± 0.27 a306.50 ± 1.70 a7.41+0.01 b
S613.60 ± 0.42 b2.81 ± 0.03 b34.52 ± 2.96 c17.83+2.29 b206.50 ± 1.70 c6.05 ± 0.03 f
Different letters indicate significant differences at p < 0.05. TN: total nitrogen; SOC: soil organic carbon; AP: available phosphorus; AK: available potassium; AN: available nitrogen.
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Song, J.; He, X.; Wang, S.; Yang, X.; Wu, L.; Li, S.; Wang, D.; Yang, M.; Wu, Z. Community Composition Specificities of Cyanobacteria in Paddy Soil under Different Ecological Conditions. Agronomy 2022, 12, 3090. https://doi.org/10.3390/agronomy12123090

AMA Style

Song J, He X, Wang S, Yang X, Wu L, Li S, Wang D, Yang M, Wu Z. Community Composition Specificities of Cyanobacteria in Paddy Soil under Different Ecological Conditions. Agronomy. 2022; 12(12):3090. https://doi.org/10.3390/agronomy12123090

Chicago/Turabian Style

Song, Jian, Xu He, Shuwen Wang, Xue Yang, Lei Wu, Siyuan Li, Dongchao Wang, Meiying Yang, and Zhihai Wu. 2022. "Community Composition Specificities of Cyanobacteria in Paddy Soil under Different Ecological Conditions" Agronomy 12, no. 12: 3090. https://doi.org/10.3390/agronomy12123090

APA Style

Song, J., He, X., Wang, S., Yang, X., Wu, L., Li, S., Wang, D., Yang, M., & Wu, Z. (2022). Community Composition Specificities of Cyanobacteria in Paddy Soil under Different Ecological Conditions. Agronomy, 12(12), 3090. https://doi.org/10.3390/agronomy12123090

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