Effects of Rice Growth Stages on the Composition and Functional Potentialities of Rhizosphere Bacterial Community in Coupled Rice-Crab System

Yu Song1*, Yueping Wei2 and Peng Wang3

1Yalu River Basin Research Institute, Liaodong University, Dandong 118003, Liaoning, China

2Innovation and Entrepreneurship Center, Liaodong University, Dandong 118003, Liaoning, China

3School of Agriculture, Liaodong University, Dandong 118003, Liaoning, China

ABSTRACT

Co-culture of rice with aquatic animals has garnered widespread interest for its potential to control soil-borne diseases, improve soil quality and increase rice yields. Therefore, it is necessary to further explore its mechanism. In this study, the samples of different growth stages of rice, including tillering stage (TS), jointing stage (JS), heading stage (HS) and mature stage (MS) were collected to analyze the impact on the community composition, diversity and functional potentialities of the rhizosphere bacterial in the coupled rice-crab system were investigated through 16S rRNA gene high-throughput sequencing. The results showed that, a total of 444,882 sequences from 12 samples were obtained, and 6637 bacterial operational taxonomic units (OTUs) with 97% sequence similarity were identified. The rhizosphere bacterial communities were more influenced by growth stages of rice than chemical properties. Principal component analysis (PCA) revealed the similarity of samples at four growth stages was significantly low (P <0.05). The dominant taxa phyla for bacterial community were similar in different growth stages. The LefSe analysis indicated that 32 distinctly taxa that were abundant among four stages with a linear discriminant analysis (LDA) score higher than 3.5. The α-diversity of the bacterial community in rhizosphere soil was not significantly different among different growth stages (P >0.05). Moreover, 8 functional potentials among 46 KEGG pathways showed notable differences for the rhizosphere bacterial community and HS had the largest number of species and strongest metabolic function potentials. Overall, the findings in this study provide valuable information for maintaining soil ecosystem balance and provide theoretical guidance for the practical application of this co-culture system.

Article Information

Received 22 February 2022

Revised 25 February 2023

Accepted 20 April 2023

Available online 12 May 2023

(early access)

Published 13 December 2023

Authors’ Contribution

Data curation: YW. Formal analysis: YS. Funding acquisition: YS. Investigation: YW, PW. Methodology: YS. Project administration: YS. Resources: PW. Software: PW. Supervision: YW. Validation: PW. Writing original draft: YS. Writing review and editing: YS. All authors have read and agreed to the published version of the manuscript.

Key words

Illumina sequencing, Different grow stages, Rhizosphere soil, Coupled rice-crab system, Bacterial community structure, Bacterial community functional potentialities

DOI: https://dx.doi.org/10.17582/journal.pjz/20220222030200

* Corresponding author: [email protected]

0030-9923/2024/0001-0173 $ 9.00/0

Copyright 2024 by the authors. Licensee Zoological Society of Pakistan.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

INTRODUCTION

Rice (Oryza sativa L.) is one of the most widely cultivated food crop worldwide, with the largest planting area in China. In recent decades, excessive application of chemical fertilizers to increase crop productivity has led to environmental and ecological concerns, such as soil acidification and soil health deterioration (Abάn et al., 2021), which poses a threat to the sustainable development of agriculture. These soil management and land-use practices seriously affect soil quality and health, and lead to nutrient loss, decreased diversity and abundance of soil biota, loss of functional biodiversity and deterioration of ecosystem services they regulate (de Vries et al., 2013). In recent years, the co-culture of rice with ecologically friendly aquatic animals such as crabs, fish, frogs, river crabs, and turtle shrimps, has been proved to be a promising option for enhancing soil quality and soil health. Studies have shown that such animals have the ability to prevent soil-borne diseases, reduce the use of chemical fertilizers, minimize environmental pollution, and promote microbiological diversity and rice yield (Bashir et al., 2020; Huang et al., 2022; Hu et al., 2020). The dominant bacterial phyla in paddy soil includes Chloroflexi, Actinobacteria, Proteobacteria, Acidobacteria, etc., which play a crucial role in soil nutrient cycling (Herlambang et al., 2021; Arunrat et al., 2022).

The rhizosphere is a critical component of the agroecosystem, comprising the soil surrounding plant roots that is influenced by plant root exudates, abscission, and plant residues. Plant roots secrete various metabolites, such as organic acids and carbohydrates, providing suitable conditions for growth and reproduction of soil microorganisms, which makes the rhizosphere contains an abundant and diverse microbial population. In the agroecosystems, rhizosphere microbiota has a profound impact on crop growth, nutrition and health (Philippot et al., 2013). Rhizosphere bacteria play an important role in the decomposition of organic matter, nutrient transformation, disease control and plant immunity improvement, but are sensitive to environmental changes (Degens et al., 2000; Mendes et al., 2011; Zamioudis and Pieterse, 2012). Cultivable microorganisms under laboratory conditions represent only a small percentage of the soil microbial population, which limits the more detailed study of rhizosphere microorganisms. The emergence of high-throughput technologies makes it possible to study previously uncultivable and rare microbial populations (DeLong, 2004; Sogin et al., 2006; Campbell et al., 2011), not only can distinguish relative abundance and evolutionary relationships, but also can insight into the diversity and species composition of microbial communities, as well as their classification and phylogeny (McHugh and Schwartz, 2016; Si et al., 2018; Li et al., 2021).

The integrated agri-aquaculture system (IAAS) ensures food security and promots sustainable agricultural development by connecting aquaculture with agricultural systems (Lansing and Kremer, 2011; Hu et al., 2016). Such system can reduce green gas emissions, increase farm productivity, and improve resource utilization efficiencies (Bashir et al., 2020). Therefore, as one of the most important aquatic ecosystem, the coupled rice-crab system has the potential to reduce the need for herbicides, pesticides and chemical fertilizer, and to stimulate the growth of rice through their uninterrupted activities. Therefore, it has gained increasing attentions due to its ability to increase soil nutrient levels and improve nutrient accumulation (Xu et al., 2019; Song et al., 2019), and has been applied in northern China.

Many studies have investigated the diversity and composition of bacterial community in paddy soil. Previous study indicated that straw returning in the rice-crayfish integrated system could improve microbial community functional diversity, contributing to the improvement of soil quality and the long-term sustainable development of the rice-crayfish integrated system (Zhu et al., 2022). Chen et al. (2021) demonstrated that the rice-turtle integrated system could effectively improve soil nutrients, and paddy field with low stocking density of Chinese soft-shelled turtles exhibited relatively high soil microbial diversity. Fernández-Baca et al. (2021) studied changes in rhizosphere soil microbial communities during plant developmental stages of high and low methane-emitting rice genotypes, contributing to determine the period of high methane emission and reduce methane emission from rice fields by screening rice varieties with low abundance methanogenic bacteria and high abundance methanogenic bacteria during this period. However, the effects of different growth stages on the structure and functional potentialities of bacterial communities in the rhizosphere soil of coupled rice-crab system is yet to be adequately investigated. The Gaijiaba organic planting farm in Beijingzi town, Donggang city, Liaoning province has been producing organic rice by culturing paddy fields with aquatic animals in recent years. Previous study have confirmed that river-crab coculture paddy fields have a better ecological basis for soil bacterial (Song et al., 2020).

In this study, the influences of different growth stages of rice on the structure and functional potentialities of bacterial communities in rhizosphere soil of the coupled rice-crab system was analysed. This study aims to identify the main driving rhizosphere bacterial communities in the coupled rice-crab system, to evaluate the diversity, structure and potential functions of the rhizosphere soil bacterial community at the different growth stages, and to distinguish the dominant bacterial population, the main functional potentials and the growth stage with the highest potential functions in the rhizosphere soil. This study provides valuable information for the practical application of this co-culture system and contributes to the understanding of maintaining soil ecosystem balance.

MATERIALS AND METHODS

Study area

The field study was conducted at the Gaijiaba Organic Planting Farm, located in Beijingzi, Donggang city, Liaoning province (39°54’ N, 123°50’ E), China from May to October 2020. This area has a continental monsoon climate, with an average annual precipitation of 888 mm and temperature of 8.4°C. The soil type was coastal saline paddy soil, with a pH of 7.1, total nitrogen (TN) of 1460 mg/kg, available phosphorus (AP) of 31.39 mg/kg, and available potassium (AK) of 126.7 mg/kg.

The main experimental plot (about 1000 m2) (Supplementary Fig. S1) was divided into 3 plots, each with a width of 15 m and length of 20 m. The rice variety used in this study was the Japanese high quality rice variety Yueguang. Rice seedlings were transplanted on May 10, 2020, with a plant to plant and row to row spacing of 15cm × 30cm. A week following transplantation, Chinese mitten crabs (Eriocheir sinensis) with an average weight of 23.1 ± 0.8 g for females and 20.8 ± 0.7 g for males, sourced from the Panjin river crab breeding base, were randomly distributed in the paddy fields at a ratio of 1:1 and the throwing density was about 450 crabs/667m2 (Zheng et al., 2019). The paddy field was surrounded by blue polyethylene escape film and equipped with a circular ladder-shaped temporary breeding pond, which could provide fish and shrimp, green feed or high-protein concentrate feed for river crabs. The seaweed biological organic fertilizer produced by Yikang Organic Agricultural Science and Technology Development Co., Ltd. (Rizhao, China) was applied in March and July respectively to provide nutrients for paddy field, regulate water quality of paddy field and enhance rice disease resistance. The crabs would be co-cultured with rice plants until the harvest on October 25, 2020.

Soil samples collection

Rhizosphere soil samples were collected from each plot using a five-point sampling method at four growth stages: the tillering stage (June 29, 2020), jointing stage (July 31, 2020), heading stage (September 2, 2020) and mature stage (October 15, 2020), which were named as TS, JS, HS and MS, respectively. The rice plants were carefully dug out to keep the intact roots and bulk soil shaken off, the rhizosphere soil closely adhering to the root surface of about 2 mm was collected using a sterile brush. Three biological replicates were collected at each growth stage and each replicate was mixed by five sub-samples. The soil samples were then divided into two parts, with one part utilized for soil chemical property determination, and the other part stored at -80°C for DNA extraction.

Determination of chemical properties of rhizosphere soil

The soil samples were air-dried, crushed, and sieved through a 2 mm sieve. Soil pH was determined using a 1:5 soil/water suspension. The content of soil organic matter (SOM) was measured by potassium dichromate oxidation method (Liu et al., 2020). The content of AK was extracted using ammonium acetate solution and determined by flame photometry (Zhao et al., 2004). The content of soil AP was determined by NaHCO3 extraction molybdenum antimony colorimetry method (Zhang et al., 2019). The content of soil TN was determined using the Kjeldahl method (Bremner, 1960).

DNA extraction, PCR amplification and high-throughput sequencing

Rhizospheric soil DNA extraction was extracted from 0.5 g of each soil sample using the E.Z.N.A.® soil DNA kit (Omega Bio-tek, Norcross, GA, USA). The V3-V4 hypervariable region of the bacterial 16S rRNA gene were amplified with the primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) using an ABI GeneAmp® 9700 PCR system (Applied Biosystems, Foster City, CA, USA). The amplification procedure was: pre-denaturation at 95°C for 2 min; denatured at 95°C for 30 s, annealed at 55°C for 30 s, extended at 72°C for 30 s, lasting for 25 cycles; finally, extended at 72°C for 5 min. PCR products were obtained and then quantified using the QuantiFluor ST blue fluorescence quantitative system (Promega, Madison, WI, USA). Finally, the DNA was mixed in corresponding proportions and sequenced using the Illumina MiSeq 300 platform (Meiji biology Co., Ltd., Shanghai, China). The paired-end reads for each sample were merged using FLASH v1.2.11 (Magoč and Salzberg, 2011), the filtered sequences were clustered into operational taxonomic units (OTUs) with a 97% similarity threshold using UPARSE 7.0.1090 (Edgar, 2013). The representative OUT sequence was annotated using the SILVA database v.138 (https://www.arb-silva.de/).

Data analysis

Venn diagram of the common and specific OTUs among groups were drawn using R software (v3.3.1, http://www.R-project.org/). Alpha diversity of rhizosphere soil bacterial communities, including Chao1 and Shannon indices, was analyzed using Mothur software (v1.30.2, https://www.mothur.org/). Statistical significance determined by one-way analysis of variance (ANOVA) for α-diversity. QIIME software (v1.9.1) was used to conduct PCA analysis to show the beta diversity of the bacterial community at different stages (Caporaso et al., 2010). The linear discriminant analysis (LDA) effect size (LEfSe) was applied to identify taxa with statistical differences (LDA score >3.5, P <0.01), and the correlations between the rhizosphere soil bacterial communities and soil chemical properties (SOM, pH, TN, AP, AK) were evaluated by Mantel tests (Dixon, 2003). Adonis statistical method was employed to determine the significant difference between different groups, the impact of different stages on the rhizosphere soil bacterial community was valued by Permutational multivariate analysis of variance (PERMANOVA). The cluster of orthologous groups (COG) family and KO (KEGG ortholog) information corresponding to each OTU were obtained using the PICRUST software (v1.1.0) and PICRUSt program with 3 levels of metabolic pathways was used to forecast the metabolic function of bacterial community in consideration of its effectiveness in obtaining functional predictions (Langille et al., 2013).

 

Table I. Chemical factors of rhizosphere soil at different growth stages of the coupled rice-crab system.

Stage	pH	AP (mg/kg)	AK (g/kg)	SOM (g/kg)	TN (g/kg)
TS	6.66±0.09a	31.39±0.56ab	126.7±5.81a	25.98±3.54a	1.46±0.20ab
JS	6.03±0.19b	35.68±2.82a	112.18±36.79a	26.70±2.67ab	1.50±0.15ab
HS	6.31±0.2ab	29.55±0.86b	94.75±13.55a	31.85±2.6a	1.78±0.15a
MS	6.69±0.11a	25.76±0.65b	75.39±3.23a	20.48±1.52b	1.15±0.08b

 

TS, tillering stage; JS, jointing stage; HS, heading stage; MS, maturity stage; AP, available phosphorus; AK, available potassium; SOM, soil organic matter; TN, total nitrogen. a-b: Small letters in the same column indicate significant difference among different growth stages at P <0.05.

 

RESULTS

Rhizosphere soil chemical properties at different growth stages of coupled rice-crab system

The chemical factors of rhizosphere soil in the coupled rice-crab system changed at different growth stages (Table I). The pH at TS was significantly different from that at JS (P <0.05). The AP content decreased significantly by 20.74% at HS and 38.51% at MS compared to that at JS (P <0.05). The AK content gradually decreased with the growth and development of rice, but there was no significant difference among different stages (P >0.05). The content of SOM and TN showed a trend of increasing first and then decreasing, with the highest at HS and the lowest at MS. Compared with HS, the content of SOM and TN at MS significantly decreased 55.52% and 54.78% respectively (P <0.05).

α-Diversity of bacterial community in rhizosphere soil at different growth stages

After quality control, a total of 444,882 clean sequences from 12 samples were obtained and 6637 rhizosphere soil bacterial OTUs with 97% sequence similarity were identified. 4690, 5056, 5139 and 5048 bacterial OTUs were detected at TS, JS, HS and MS, respectively (Supplementary Fig. SII). The numbers of common bacterial OTUs among the four groups were 3122; and the numbers of unique bacterial OTUs were 273, 294, 264 and 328 at TS, JS, HS and MS, respectively.

The results of the analyzed soil samples collected at different growth stages showed an insignificant change in rhizosphere soil bacterial community α-diversity indicies (ANOVA, P >0.05). The highest bacterial Chao1 index (4784.3 ± 165.89) was detected at HS, while the Chao1 indices at TS, JS and MS were 4373.45 ± 199.03, 4770.05 ± 274.37 and 4689.98 ± 303.17, respectively. Furthermore, the highest Shannon index (6.87 ± 0.06) was observed at MS, while the Shannon indices at TS, JS and HS were 6.85 ± 0.04, 6.78 ± 0.11 and 6.80 ± 0.09, respectively (Table II).

 

Table II. Chao1 and Shannon indices of rhizosphere soil bacterial community at four different stages in the coupled rice-crab system.

Indices	TS	JS	HS	MS
Chao1	4373.45± 199.03	4770.05± 274.37	4784.3± 165.89	4689.98± 303.17
Shannon	6.85±0.04	6.78±0.11	6.80±0.09	6.87±0.06

 

Notes: Values are mean ± standard deviations (SD).

Factors driving rhizosphere soil bacterial communities in different stages of paddy fields

The influence of all driving factors including rhizosphere soil chemical properties and different stages on the bacterial communities was investigated. The result of Mantel test (Supplementary Table SI) indicated that the rhizosphere soil chemical properties had little correlation with bacterial communities (Mantel test, R2 = 0.227, P >0.05), whereas the different stages explained 55.7% of variance in bacteria (PERMANOVAs, R2 = 0.557, P = 0.034 <0.05). The PCA results showed that the structure of bacterial communities at four growth stages were significantly different (Fig. 1, R2 = 0.5663, Adonis test, P = 0.001).

 

Composition of the rhizosphere soil bacterial community

Dynamic changes of species at different classification levels were assessed (Fig. 2). There were 10 dominant bacterial phyla accounted for 91% of the whole rhizosphere soil bacterial composition. Chloroflexi, Actinobacteriota, Proteobacteria and Acidobacteriota were the top four predominant phyla in all samples, accounting for 18.72~28.25%, 13.20~22.61%, 12.27~19.41%, 11.29~14.04% respectively (Fig. 2A). Chloroflexi was the most dominant bacterial phylum in all four samples, but with no significant difference at four stages. In addition, Actinobacteriota, Proteobacteria, Desulfobacterota, Firmicutes and Genmatimonadota were significantly different among four different stages (ANOVA, P <0.05) (Supplementary Fig. S3A). The most abundant classes were Anaerolineae (12.56%), Gammaproteobacteria (9.18%), Actinobacteria (8.99%), Alphaproteobacteria (6.56%) and KD-4-96 (6.33%) (Fig. 2B).

Across the four stages in the main bacterial class, Gammaproteobacteria, Actinobacteria, Alphaproteobacteria and Bacteroidia were remarkably different (ANOVA, P <0.05) (Supplementary Fig. S3B). The norank_fnorank_o_norank_c_KD4-96 (3.86%~8.38%), norank_f_norank_o_RBG-13-54-9 (2.43%~4.10%), norank_f_norank_o_Gaiellales (2.73%~3.97%), norank_f_norank_o_Vicinamibacterales (2.03%~3.36%), norank_f_Anaerolineaceae (1.84%~3.48%) were the top 5 genus at four stages in all samples (Fig. 2C) and norank_f_norank_O_RBG-13-54-9 was the only genus with notable difference among the four stages (ANOVA, P <0.05) (Supplementary Fig. S3C).

 

 

LEfSe of the bacterial communities in the rhizosphere of the four stages in the crab-rice paddy fields

Taxa with significant differences among TS, JS, HS and MS were detected by LEfSe (Fig. 3). The LEfSe results indicated that 32 taxa were enriched among the four stages when the LDA score was higher than 3.5. 17 were distinctly abundant at TS, notably the phylum Actinobacteriota and Bacteroidota, the class Actinobacteria, Alphaproteobacteria and Bacteroidia and the order Micrococcales. The differentially abundant taxa at JS was the order Frankiales. The phylum Chloroflexi and the class, order, family and genus of KD4-96 were enriched taxa in HS. The class Gammaproteobacteria, the phylum Proteobacteria and the family Gallionellaceae were amplified in MS.

Function prediction of rhizosphere soil bacterial community at different growth stages of rice-crab paddy field

We used PICRUSt to predict KEGG pathways based on the OTU data. In total, 46 KEGG pathways at the 2nd level were found by PICRUSt analysis. The results demonstrated that the relative abundance of 43 pathways at HS were higher than other three stages, and the relative abundance of 8 metabolic pathways was dramatically different such as amino acid metabolism, biosynthesis of other secondary metabolites, energy metabolism, translation, replication and repair, signal transduction, lipid metabolism, cellular community-prokaryotes at four different stages (Fig. 4).

 

DISCUSSION

Many studies have been conducted on various co-culture systems for a long time, which bring many positive effects on both crops and the environment, showing significant sustainability (Herlambang et al., 2021; Bashir et al., 2020; Fierro-Sañudo et al., 2020; Feng et al., 2016; Hu et al., 2016). The rice-crab co-culture system effectively enhances rice yield and quality, while concurrently reducing the use of fertilizers and pesticides; it also improves soil quality, optimizes land use, and safeguards biodiversity (Hu et al., 2020; Jin et al., 2020; Bao et al., 2022). The co-culture of crabs can impact the composition of soil microbial communities in rice paddies (Li et al., 2021). To gain a better understanding of the dynamic changes associated with this co-culture system, this study investigated the chemical properties and bacterial communities in the rhizosphere soil, clustered at different growth stages in the coupled rice-crab paddy field. The results showed that there was no significant correlation between chemical properties and bacterial communities in rhizosphere soil. Furthermore, PERMANOVAs result showed that the different growth stages of rice explained 55.7% of the variance in bacteria. Rasche et al. (2006) indicated that bacterial community in rhizosphere of Solanum tuberosum varied significantly at different vegetation stages. Zhao et al. (2022) proved that rhizosphere bacterial community in orchard soil under a cover crop at different periods was obviously different. Thus, we deduced that the growth stage of rice may be the main factor driving rhizosphere bacterial community of the coupled rice crab system. Different growth stage had different bacterial diversity in the rhizosphere soil of the coupled rice-crab system (Chen et al., 2019; Wang et al., 2021). Previous study demonstrated that the number, species and diversity of rhizosphere microorganisms showed a dynamic change trend (Lauber et al., 2009). In our study, soil samples of the same kind of rice in the rice-crab paddy field were collected at the four different stages, to invest whether the growth stage was the main factor influencing rhizosphere bacterial diversity. The results showed that, there were the most OTUs and Chao1 index at the heading stage, indicating there were the largest number of species, meanwhile, Shannon index at maturity is the highest, showing that the species are most abundant in this period. Similarly, Xu et al. (2009) demonstrated that diversity of rhizosphere bacterial community in soybean changed with a progression in growth stage and full maturity had the highest diversity. This may be due to that the component and content of plant root exudates in different growth stages were different, which might prohibit specific rhizosphere bacterial groups, consequently affecting the diversity of bacterial community in the rhizosphere. Despite slight differences in the α-diversity indices across the different growth stages, no significant differences were observed among them, which is consistent with the results of other rice co-culture studies, including rice-fish (Arunrat et al., 2022), rice-frog (Yi et al., 2019), and rice-crab (Li et al., 2021).

In this study, in the rice-crab co-culture system, the relative abundance of the bacterial community varied with the growth stage at different taxonomic levels, and that of some predominant bacterial groups showed remarkable difference at the four stages. Distinct differences were found in the abundances of dominant bacterial phyla, Actinobacteriota was significantly abundant at TS, and the abundance of Proteobacteria at MS was high. Similarly, Ding et al. (2021) demonstrated that Proteobacteria and Actinobacteriota were the rhizosphere donimant phyla in the rice-turtle co-culture system. Moreover, Desulfobacterota was significantly enriched at MS, Firmicutes and Gemmatimonadota were also more abundant at TS than in the other stages., Actinobacteria, widely existed in soil and water ecosystems, played a key role in decomposition and humus formation, controlling plant disease, promoting plant growth and regulating the biological interactions among the microenvironment, plants, and pathogens (Buée et al., 2009; Gao et al., 2019). Johnston-Monje et al. (2016) had confirmed that environment with rich nutrient was suitable for the rapid growth of Proteobacteria. Most of Proteobacteria are gram negative bacillus, many of which are responsible for nitrogen fixation and polycyclic aromatic hydrocarbon degradation. Desulfobacterota is a kind of sulfate-reducing bacteria which is widely existed in the paddy fields. It can not only reduce sulfate to sulfide, participating in the biogeochemical cycle of sulfur soil, but also degrade cresol, biphenyl and other pollutants in paddy soil (Shibata et al., 2007; Yang et al., 2008). Firmicutes can inhibit the production and emission of methane by inhibiting the activity of methanogens and improving the redox potential of methanogenic environment through Fe(III) reduction process. (Cheng et al., 2007; Frenzel et al., 1999). Bay et al. (2021) identified phylum Gemmatimonadeota potentially capable of aerobic methanotrophy. Significant enrichment in rhizosphere soils at different stages suggested the rhizosphere could attrack specific bacteria in the different growth stages. All these results showed that growth stages could influence the composition of the rhizospheric bacterial community. LEfSe analysis showed that there were more bacterial taxa with significant differences at TS than that in other samples, which might be related to the vigorous metabolic activity of rice roots at TS (Zhang et al., 2015). PCA analysis showed that the structure of bacterial communities at four growth stages were significantly different, but the community structure between JS and HS was similar, indicating the bacterial community structure inclined to be stable and the variation was small in the middle stage of rice development. The community structure between TS and MS was a little different. Moreover, the community structure of TS and MS was different from that of JS and HS, explaining that growth stage of rice had an impact on the rhizosphere bacterial community structure.

Soil microorganisms can affect soil nutrient cycling and regulate soil function by participating in the decomposition and mineralization of soil organic matter (Romaniuk et al., 2011). Yuan et al. (2015) deduced that the continuous changes of some physicochemical factors such as the change of root structure and rhizosphere secretion caused the succession of bacterial functional structure. In this study, the PICRUSt results showed metabolic pathways at 3 levels in different growth stages of rice-crab paddy field were similar, and the metabolic function of bacteria changed in four different stages of rice development. Furthermore, the abundance of 43 metabolic pathways at the 2nd level was higher in HS than those in the other three stages and there were significant differences in 8 metabolic pathways. The rice HS is an essential phase of rice production because it can affect the rice yield directly (Bai et al., 2018). Previous study demonstrated that the community structure in the middle and late stages of rice development was relatively stable, which was different from that in the early stage (Noll et al., 2005). In this paper, the number of OTU and Chao1 index at HS were also the highest among the four growth stages, revealing that the total number of species in this period was the largest. Taken together, HS had the highest number of species and the strongest metabolic functional potentials, indicating the interrelation between bacterial community composition and function. Future studies may further explore the correlation between rhizosphere bacterial communities structure and function and rice yield in the coupled rice-crab system.

CONCLUSION

In conclusion, the results showed that the rhizosphere bacterial communities were more influenced by growth stage than chemical properties, and the bacterial community structure differed significantly among the four growth stages. At the heading stage, the bacterial community had the largest number of species and strongest metabolic function potentials. Specifically, with the OTU number and Chao1 index of 5139 and 4784.3, respectively, which were the highest at the four stages. Moreover, the relative abundance of 43 among the total 46 metabolic pathways at heading stage was higher than that of the other three stages. This study highlights the impact of rice growth stages on the composition and functional potentialities of rhizosphere bacterial communities in the coupled rice-crab system. These results provide data reference for the practical application of this co-culture system, and essential insights for maintaining soil ecosystem balance.

Funding

This work was supported by scientific research project of Liaoning Provincial Department of Education (LNSJYT202005).

IRB approval

This study did not involve human subjects.

Ethical statement

Not applicable.

Supplementary material

There is supplementary material associated with this article. Access the material online at: https://dx.doi.org/10.17582/journal.pjz/20220222030200

Statement of conflict of interest

The authors have declared no conflict of interest.

REFERENCES

Abάn, C.L., Brandan, C.P., Verdenelli, R., Huidobro, J., Meriles, J.M. and Gil, S.V., 2021. Changes in microbial and physicochemical properties under cover crop inclusion in a degraded common bean monoculture system. Eur. J. Soil Biol., 107: 103365. https://doi.org/10.1016/j.ejsobi.2021.103365

Arunrat, N., Sansupa, C., Kongsurakan, P., Sereenonchai, S. and Hatano, R., 2022. Soil microbial diversity and community composition in rice–fish co-culture and rice monoculture farming system. Biology, 11: 1242. https://doi.org/10.3390/biology11081242

Bai, X.D., Cao, Z.G., Zhao, L.D., Zhang, J.R., Lv, C.F., Li, C.N. and Xie, J.D., 2018. Rice heading stage automatic observation by multi-classifier cascade based rice spike detection method. Agric. For. Meteorol., 259: 260-270. https://doi.org/10.1016/j.agrformet.2018.05.001

Bao, J., Jiang, H. and Li, X., 2022. Thirty years of rice-crab coculture in China. Research progress and prospects. Rev. Aquacult., 14: 1597-1612. https://doi.org/10.1111/raq.12664

Bashir, M.A., Liu, J., Geng, Y., Wang, H., Pan, J., Zhang, D., Rehim, A., Aon, M. and Liu, H.B., 2020. Co-culture of rice and aquatic animals: An integrated system to achieve production and environmental sustainability. J. Cleaner Prod., 249: 119310. https://doi.org/10.1016/j.jclepro.2019.119310

Bashir, M.A., Wang, H.Y., Pan, J.T., Khoshnevisan, B., Sun, W., Zhai, L., Zhang, X., Wang, N., Rehim, A. and Liu, H., 2021. Variations in soil nutrient dynamics and their composition in rice under integrated rice crab co-culture system. J. Cleaner Prod., 281: 125222. https://doi.org/10.1016/j.jclepro.2020.125222

Bay, S.K., Dong, X.J., Bradley, J.A., Leung, P.M., Grinter, R., Jirapanjawat, T., Arndt, S.K., Cook, P.L.M., LaRowe, D.E., Nauer, P.A., Chiri, E. and Greening, C., 2021. Trace gas oxidizers are widespread and active members of soil microbial communities. Nat. Microbiol., 6: 246-256. https://doi.org/10.1038/s41564-020-00811-w

Bremner, J.M., 1960. Determination of nitrogen in soil by the Kjeldahl method. J. agric. Sci., 55: 11-33. https://doi.org/10.1017/S0021859600021572

Buée, M., Reich, M., Murat, C., Morin, E., Nilsson, R.H., Uroz, S. and Martin, F., 2009. 454 Pyrosequencing analyses of forest soils reveal an unexpectedly high fungal diversity. New Phytol., 184: 449-456. https://doi.org/10.1111/j.1469-8137.2009.03003.x

Campbell, B.J., Yu, L., Heidelberg, J.F. and Kirchman, D.L., 2011. Activity of abundant and rare bacteria in a coastal ocean. Proc. natl. Acad. Sci. U.S.A., 108: 12776-12781. https://doi.org/10.1073/pnas.1101405108

Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., Fierer, N., Peña, A.G., Goodrich, J.K., Gordon, J.I., Huttley, G.A., Kelley, S.T., Knights, D., Koenig, J.E., Ley, R.E., Lozupone, C.A., McDonald, D., Muegge, B.D., Pirrung, M., Reeder, J., Sevinsky, J.R., Turnbaugh, P.J., Walters, W.A., Widmann, J., Yatsunenko, T., Zaneveld, J. and Knight, R. 2010. QIIME allows analysis of highthroughput community sequencing data. Nat. Methods, 7: 335-336. https://doi.org/10.1038/nmeth.f.303

Chen, J., He, J.X., Wu, B.L., Huang, L. and Zhang, Y., 2021. Effects of Chinese soft-shelled turtle density on soil bacterial community structure in rice-turtle intergrowth field. J. South. Agric., 52: 2650-2661.

Chen, L., Xin, X.L., Zhang, J.B., Redmile-Gordon, M., Nie, G.S. and Wang, Q.Y., 2019. Soil characteristics overwhelm cultivar effects on the structure and assembly of root-associated microbiomes of modern maize. Pedosphere, 29: 360-373. https://doi.org/10.1016/S1002-0160(17)60370-9

Cheng, W., Yagi, K., Akiyama, H., Nishimura, S., Sudo, S., Fumoto, T., Hasegawa, T., Hartley, A.E. and Megonigal, J.P., 2007. An empirical model of soil chemical properties that regulate methane production in Japanese rice paddy soils. J. environ. Qual., 36: 1920. https://doi.org/10.2134/jeq2007.0201

de Vries, F.T., Thébault, E., Liiri, M., Birkhofer, K., Tsiafouli, M.A., Bjørnlund, L., Jørgensen, H.B., Brady, M.V., Christensen, S., de Ruiter, P.C., d’Hertefeldt, T., Frouz, J., Hedlund, K., Hemerik, L., Gera Hol, W.H., Hotes, S., Mortimer, S.R., Setälä, H., Sgardelis, S.P., Uteseny, K., van der Putten, W.H., Wolters, V. and Bardgett, R.D., 2013. Soil food web properties explain ecosystem services across European land use systems. Proc. natl. Acad. Sci. U.S.A., 110: 14296-14301. https://doi.org/10.1073/pnas.1305198110

Degens, B.P., Schipper, L.A., Sparling, G.P. and Vojvodic-Vukovic, M., 2000. Decreases in organic C reserves in soils can reduce the catabolic diversity of soil microbial communities. Soil Biol. Biochem., 32: 189-196. https://doi.org/10.1016/S0038-0717(99)00141-8

DeLong, E.F., 2004. Microbial population genomics and ecology: The road ahead. Environ. Microbiol., 6: 875-878. https://doi.org/10.1111/j.1462-2920.2004.00668.x

Ding, J.L., Meng, X.J., Wang, R., Chen, L., Zhou, J., Chen, C. and Huang, H., 2021. Effects of long-term application of rice-turtle co-culture on soil bacterial community structure and diversity. J. South Agric., 52: 1860-1868.

Dixon, P., 2003. VEGAN, a package of R functions for community ecology. J. Veg. Sci., 14: 927-930. https://doi.org/10.1111/j.1654-1103.2003.tb02228.x

Edgar, R.C., 2013. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods, 10: 996-998. https://doi.org/10.1038/nmeth.2604

Feng, J., Li, F., Zhou, X., Xu, C. and Fang, F., 2016. Nutrient removal ability and economical benefit of a rice-fish co-culture system in aquaculture pond. Ecol. Eng., 94: 315-319. https://doi.org/10.1016/j.ecoleng.2016.06.002

Fernández-Baca, C.P., Rivers, A.R., Kim, W., Iwata, R., McClung, A.M., Roberts, D.P., Reddy, V.R. and Barnaby, J.Y., 2021. Changes in rhizosphere soil microbial communities across plant developmental stages of high and low methane emitting rice genotypes. Soil Biol. Biochem., 156: 108233. https://doi.org/10.1016/j.soilbio.2021.108233

Fierro-Sañudo, J.F., Rodríguez-Montes de Oca, G.A. and Páez-Osuna, F., 2020. Co-culture of shrimp with commercially important plants: A review. Rev. Aquacult., 12: 2411-2428. https://doi.org/10.1111/raq.12441

Frenzel, P., Bosse, U. and Janssen, P.H., 1999. Rice roots and methanogenesis in a paddy soil: Ferric iron as an alternative electron acceptor in the rooted soil. Soil Biol. Biochem., 31: 421-430. https://doi.org/10.1016/S0038-0717(98)00144-8

Gao, X.N., Wu, Z.L., Liu, R., Wu, J.Y., Zeng, Q.Y. and Qi, Y.W., 2019. Rhizosphere bacterial community characteristics over different years of sugarcane ratooning in consecutive monoculture. BioMed. Res. Int., 2019: 4943150. https://doi.org/10.1155/2019/4943150

Herlambang, A., Murwantoko, M. and Istiqomah, I., 2021. Dynamic change in bacterial communities in the integrated rice–fish farming system in Sleman, Yogyakarta, Indonesia. Aquacult. Res., 52: 5566-5578. https://doi.org/10.1111/are.15432

Hu, L.L., Guo, L., Zhao, L.F., Shi, X.Y., Ren, W.Z., Zhang, J., Tang, J.J. and Chen, X., 2020. Productivity and the complementary use of nitrogen in the coupled rice-crab system. Agric. Syst., 178: 102742. https://doi.org/10.1016/j.agsy.2019.102742

Hu, L.L., Zhang, J., Ren, W.Z., Guo, L., Cheng, Y.X., Li, J.Y., Li, K.X., Zhu, Z.W., Zhang, J.E., Luo, S.M., Cheng, L., Tang, J.J. and Chen, X., 2016. Can the co-cultivation of rice and fish help sustain rice production? Sci. Rep., 6: 28728. https://doi.org/10.1038/srep28728

Huang, X.L., Li, M.H., Huang, Y., Yang, H., Geng, Y., Ouyang, P., Chen, D.F., Yin, L.Z., Yang, S.Y., Jiang, J., Luo, W. and He, Z., 2022. Microbiome analysis reveals microecological advantages of emerging ditchless rice-crayfish co-culture mode. Front. Microbiol., 13: 892026. https://doi.org/10.3389/fmicb.2022.892026

Jin, T., Ge, C., Gao, H., Zhang, H. and Sun X., 2020. Evaluation and screening of co-culture farming models in rice field based on food productivity. Sustainability, 12: 2173. https://doi.org/10.3390/su12062173

Johnston-Monje, D., Lundberg, D.S., Lazarovits, G., Reis, V.M. and Raizada, M.N., 2016. Bacterial populations in juvenile maize rhizospheres originate from both seed and soil. Pl. Soil, 405: 337-355. https://doi.org/10.1007/s11104-016-2826-0

Langille, M.G.I., Zaneveld, J., Caporaso, J.G., McDonald, D., Knights, D., Reyes, J.A., Clemente, J.C., Burkepile, D.E., Thurber, R.L.V., Knight, R., Beiko, R.G. and Huttenhower, C., 2013. Predictive functional profifiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol., 31: 814-821. https://doi.org/10.1038/nbt.2676

Lansing, J.S. and Kremer, J.N., 2011. Rice, fish, and the planet. Proc. natl. Acad. Sci., 108: 19841-19842. https://doi.org/10.1073/pnas.1117707109

Lauber, C.L., Hamady, M., Knight, R. and Noah, F., 2009. Pyrosequencing based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale. Appl. environ. Microbiol., 75: 5111-5120. https://doi.org/10.1128/AEM.00335-09

Li, Y.D., Li, L.S., Yu, Y.L., Hu, Q.B. and Li, X.D., 2021. Impact of dietary protein content on soil bacterial and fungal communities in a rice–crab co-culture system. Front. Microbiol., 12: 696427. https://doi.org/10.3389/fmicb.2021.696427

Liu, J., Wang, Z., Hu, F., Xu, C., Ma, R. and Zhao, S., 2020. Soil organic matter and silt contents determine soil particle surface electrochemical properties across a long-term natural restoration grassland. Catena, 190: 104526. https://doi.org/10.1016/j.catena.2020.104526

Magoč, T. and Salzberg, S.L., 2011. Flash: Fast length adjustment of short reads to improve genome assemblies. Bioinformatics, 27: 2957-2963. https://doi.org/10.1093/bioinformatics/btr507

McHugh, T.A. and Schwartz, E.A., 2016. A watering manipulation in a semiarid grassland induced changes in fungal but not bacterial community composition. Pedobiologia, 59: 121-127. https://doi.org/10.1016/j.pedobi.2016.04.003

Mendes, R., Kruijt, M., de Bruijn, I., Dekkers, E., van der Voort, M., Schneider, J.H., Piceno, Y.M., DeSantis, T.Z., Andersen, G.L., Bakker, P.A. and Raaijmakers, J.M., 2011. Deciphering the rhizosphere microbiome for disease-suppressive bacteria. Science, 332: 1097-1100. https://doi.org/10.1126/science.1203980

Noll, M., Matthies, D., Frenzel, P., Derakshani, M. and Liesack, W., 2005. Succession of bacterial community structure and diversity in a paddy soil oxygen gradient. Environ. Microbiol., 7: 382–395. https://doi.org/10.1111/j.1462-2920.2005.00700.x

Philippot, L., Raaijmakers, J.M., Lemanceau, P. and van der Putten, W.H., 2013. Going back to the roots: The microbial ecology of the rhizosphere. Nat. Rev. Microbiol., 11: 789-799. https://doi.org/10.1038/nrmicro3109

Rasche, F., Hödl, V., Poll, C., Kandeler, E., Gerzabek, M.H., van Elsas, J.D. and Sessitsch, A., 2006. Rhizosphere bacteria affected by transgenic potatoes with antibacterial activities compared with the effects of soil, wild-type potatoes, vegetation stage and pathogen exposure. FEMS Microbiol. Ecol., 56: 219-235. https://doi.org/10.1111/j.1574-6941.2005.00027.x

Romaniuk, R., Giuffre, L., Costantini, A. and Nannipieri, P., 2011. Assessment of soil microbial diversity measurements as indicators of soil functioning in organic and conventional horticulture systems. Ecol. Indic., 11: 1345-1353. https://doi.org/10.1016/j.ecolind.2011.02.008

Shibata, A., Toyota, K., Miyake, K. and Katayama, A., 2007. Anaerobic biodegradation of 4-alkylphenols in a paddy soil microcosm supplemented with nitrate. Chemosphere, 68: 2096-2103. https://doi.org/10.1016/j.chemosphere.2007.02.007

Si, Z.H., Song, X.S., Wang, Y.H., Cao, X., Zhao, Y.F., Wang, B.D., Chen, Y. and Arefe, A., 2018. Intensified heterotrophic denitrification in constructed wetlands using four solid carbon sources denitrification efficiency and bacterial community structure. Bioresour. Technol., 267: 416-425. https://doi.org/10.1016/j.biortech.2018.07.029

Sogin, M.L., Morrison, H.G., Huber, J.A., Welch, D.M., Huse, S.M., Neal, P.R., Arrieta, J.M. and Herndl, G.J., 2006. Microbial diversity in the deep sea and the underexplored rare biosphere. Proc. natl. Acad. Sci. U.S.A., 103: 12115-12120. https://doi.org/10.1073/pnas.0605127103

Song, C., Zhang, J., Hu, G., Meng, S., Fan, L., Zheng, Y., Fan, L., Zheng, Y., Chen, J.Z. and Zhang, X.W., 2019. Risk assessment of chlorantraniliprole pesticide use in rice-crab coculture systems in the basin of the lower reaches of the Yangtze River in China. Chemosphere, 230: 440-448. https://doi.org/10.1016/j.chemosphere.2019.05.097

Song, Y., Wang, P. and Wei, Y.P., 2020. Analysis on diversity of soil community under different paddy field cultivation patterns. Southwest China J. agric. Sci., 33: 263-267.

Wang, H., Fang, X., Wu, H., Cai, X.Y. and Xiao, H.X., 2021. Effects of plant cultivars on the structure of bacterial and fungal communities associated with ginseng. Pl. Soil, 465: 143-156. https://doi.org/10.1007/s11104-021-05000-0

Xu, Q., Wang, X., Xiao, B. and Hu, K., 2019. Rice-crab coculture to sustain cleaner food production in Liaohe River Basin, China: An economic and environmental assessment. J. Cleaner Prod., 208: 188-198. https://doi.org/10.1016/j.jclepro.2018.10.092

Xu, Y.X., Wang, G.H., Jin, J., Liu, J.J., Zhang, Q.Y. and Liu, X.B., 2009. Bacterial communities in soybean rhizosphere in response to soil type, soybean genotype, and their growth stage. Soil Biol. Biochem., 41: 919-925. https://doi.org/10.1016/j.soilbio.2008.10.027

Yang, S., Yoshida, N., Baba, D. and Katayama, A., 2008. Anaerobic biodegradation of biphenyl in various paddy soils and river sediment. Chemosphere, 71: 326-336. https://doi.org/10.1016/j.chemosphere.2007.09.002

Yi, X., Yi, K., Fang, K., Gao, H., Dai, W. and Cao, L., 2019. Microbial community structures and important associations between soil nutrients and the responses of specific taxa to rice-frog cultivation. Front. Microbiol., 10: 1752. https://doi.org/10.3389/fmicb.2019.01752

Yuan, J., Chaparro, J.M., Manter, D.K., Zhang, R.F., Vivanco, J.M. and Shen, Q., 2015. Roots from distinct plant developmental stages are capable of rapidly selecting their own microbiome without the influence of environmental and soil edaphic factors. Soil Biol. Biochem., 89: 206-209. https://doi.org/10.1016/j.soilbio.2015.07.009

Zamioudis, C. and Pieterse, C.M., 2012. Modulation of host immunity by beneficial microbes. Mol. Pl. Microbe Interact., 25: 139-150. https://doi.org/10.1094/MPMI-06-11-0179

Zhang, T., Wang, Z.K., Lv, X.H., Li, Y. and Zhuang, L., 2019. High-throughput sequencing reveals the diversity and community structure of rhizosphere fungi of Ferula Sinkiangensis at different soil depths. Sci. Rep., 9: 6558. https://doi.org/10.1038/s41598-019-43110-z

Zhang, Z.X., Zhang, W.Z., Yang, H.C., Chen, C.L. and Wei, W.X., 2015. Effects of growing rice roots on the bacterial abundance and community structure in the rhizosphere during tillering stage. Acta agric. Zhejiangensis, 27: 2045-2052.

Zhao, Z.Q., Zhu, Y.G., Li, H.Y., Smith, S.E. and Smith, F.A., 2004. Effects of forms and rates of potassium fertilizers on cadmium uptake by two cultivars of spring wheat (Triticum aestivum L.). Environ. Int., 29: 973-978. https://doi.org/10.1016/S0160-4120(03)00081-3

Zhao, Z.Y., Ma, Y.T., Feng, T.Y., Kong, X., Wang, Z.H., Zheng, W. and Zhai, B.N., 2022. Assembly processes of abundant and rare microbial communities in orchard soil under a cover crop at different periods. Geoderma, 406: 115543. https://doi.org/10.1016/j.geoderma.2021.115543

Zheng, Y., Liu, X., Geng, D., Xu, X.F. and Li, Y., 2019. Effects of stocking density of larval crab on the benefit of adult crab culture in paddy fields. Hunan agric. Sci., 8: 74-77.

Zhu, X.X., Peng, C.L., Si, G.H., Sha, A.H., Yuan, J.F., Zhao, S.J., Xu, D.B. and Liu, W., 2022. Effects of straw returning on soil chemical properties and microbial community diversity under the rice-crayfish integrated system. Sustainability, 14: 13539. https://doi.org/10.3390/su142013539