Impact of Different Water Management Cultivation Methods on the Rhizosphere Bacteria Community of Shanlan Upland Rice

doi:10.13560/j.cnki.biotech.bull.1985.2023-0884

Abstract

Abstract:

【Objective】 The cultivation way of Shanlan upland rice is single, and the traditional slash and burn cultivation method damages the environment. Cultivation in water can be a new way for Shanlan upland rice. This work is to explore the changes in rhizosphere microorganisms of Shanlan upland rice under water cultivation environment in large fields. 【Method】 The cultivation treatment of Shanlan upland rice was set up with normal irrigation and drying management, and 16S rRNA gene amplification sequencing was performed on the bacterial community in the rhizosphere soil of Shanlan upland rice. The sequencing data was combined with soil physicochemical properties for comprehensive analysis. 【Result】 The changes in cultivation methods have significantly affected the composition of rhizosphere bacterial communities. In particular, the relative abundance of Nitrosprota and Proteobacteria in the normal irrigation is lower than that in the drying management, and the relative abundance of Firmicutes is higher than that in drying management. The top 10 bacterial communities with relative abundance are correlated with soil environmental factors. The correlation network analysis shows that more bacterial communities interact in normal irrigation, and there is a more complex bacterial network under normal irrigation. 【Conclusion】 Significant changes in bacterial community composition occure in the rhizosphere of Shanlan upland rice under different water management cultivation methods. The bacteria groups of Nitrospirota and Proteobacteria may improve the stress resistance of Shanlan upland rice by promoting nitrogen uptake at the root of rice. In normal irrigation, more bacterial community interactions enhance the stability of the ecosystem.

Key words: Shanlan upland rice, cultivation methods, rhizosphere microorganisms, soil physicochemical properties

LIU Jia-ning, LI Meng, YANG Xin-sen, WU Wei, PEI Xin-wu, YUAN Qian-hua. Impact of Different Water Management Cultivation Methods on the Rhizosphere Bacteria Community of Shanlan Upland Rice[J]. Biotechnology Bulletin, 2024, 40(3): 242-250.

Figures/Tables 10

Fig. 1 Effect of irrigated and drying treatment on the relative abundance of bacterial community in rhizosphere soil at phylum level The abscissa refers to treatment, H to drying management treatment, and S to normal irrigation treatment. The ordinate is the relative abundance percentage. Different colors indicate different bacterial phyla. The stacked column is a taxon with a relative abundance of top 10 at the phylum level

Fig. 2 Box graph of differences in alpha diversity index between irrigated and drying treatment groups The abscissa refers to the grouping name, H to drying management treatment, S to normal irrigation treatment, and the ordinate refers to the value of alpha diversity index. The upper and lower sides of the box: the upper quartile and the lower quartile（IQR）; middle line: the median of the sample; upper and lower margins: maximum and minimum inner circumference（IQR×1.5）. The outer points of the edges indicate abnormal values. The number on the line between the two columns is the P-value of the t-test represent outliers

Fig. 3 PcoA analysis Each point in the figure indicates a sample. The blue dot represents drying management treatment, and the orange dot represents normal irrigation treatment. An elliptical circle indicates that it is a 95% confidence interval. The abscissa PC1 is the first principal component, and the percentage is the contribution rate of the first principal component to the sample difference. The ordinate PC2 is the second principal component. Percentage is the contribution rate of the second principal component to the sample difference

Fig. 4 PERMANOVA analysis box diagram A: Treatment; B: variety. The ordinate indicates the Bray-Curtis distance. The box diagram above “All between *” indicates the beta distance data of all inter group samples. The box chart below shows the beta distance data between samples in the group treated with drying management and normal irrigation, respectively. H refers to drying management treatment, and S to normal irrigation treatment. R2 is the degree of explanation for sample differences

Fig. 5 Sample community distribution map of species evolution tree The legend in the upper right corner shows the names of species at the phylum level, the inner circle shows the evolutionary tree of species, and the same phylum in the inner circle is in the same color. The outer circle indicates the relative abundance proportion of this species in different treatments. H: Drying management. S: Normal irrigation.

Table 1 Bacterial phylum communities with significant differences in different water management cultivation treatments

细菌门 Bacterial phylum	相对丰度Relative abundance		P
细菌门 Bacterial phylum	正常灌溉 Normal irrigation	干旱管理 Drought management	P
Acidobacteriota	0.091 4	0.075 5	<0.01
Armatimonadota	0.003 4	0.001 6	<0.01
Bdellovibrionota	0.006 3	0.011 3	<0.01
Sumerlaeota	0.001 3	0.002 2	<0.01
Planctomycetota	0.016 8	0.032 5	<0.01
Dadabacteria	0.003 3	0.009 1	<0.01
Dependentiae	0.004 0	0.007 9	<0.01
Entotheonellaeota	0.000 1	0.000 4	<0.01
Fibrobacterota	0.002 7	0.001 4	<0.01
Patescibacteria	0.014 2	0.030 2	<0.01
Nitrospirota	0.069 1	0.098 9	<0.01
Myxococcota	0.063 3	0.045 1	<0.01
Methylomirabilota	0.005 8	0.008 8	<0.01
Gemmatimonadota	0.012 2	0.007 9	<0.01
Verrucomicrobiota	0.046 8	0.037 5	<0.01
Calditrichota	0.000 6	0.001 5	<0.01
Firmicutes	0.140 5	0.107 7	<0.01
Proteobacteria	0.157 5	0.178 6	<0.01
Hydrogenedentes	0.000 6	0.000 9	0.02

Table 2 Differences in soil environmental factors under different water management cultivation treatments

环境因子 Environmental factor	正常灌溉 Normal irrigation	干旱管理 Drought management	P
有效钾/（mg·kg^-1）	69.99 ± 0.81	68.12±0.54	0.030
有效磷/（mg·kg^-1）	3.26 ± 0.08	4.81±0.11	<0.001
有机质/（g·kg^-1）	11.85±0.19	23.30±0.03	<0.001
碱解氮/（mg·kg^-1）	63.23±1.69	117.75±1.68	<0.001
全氮/（g·kg^-1）	0.80±0.02	1.46±0.04	<0.001
pH	8.61±0.10	8.20±.030	0.003

Fig. 6 Heat map of correlation between environmental factors and the top ten bacterial communities with relative abundance The abscissa refers to various environmental factors; AK（available potassium）, pH, AP（available phosphorus）, OM（organic matter）, AN（alkali hydrolyzed nitrogen）, TN（total nitrogen）.The vertical coordinate is the top ten bacterial communities with relative abundance. Red indicates positive correlation. Blue indicates negative correlation. The color depth indicates the correlation size. The significance is indicated by *，* indicates that the P-value < 0.05, ** indicates that the P-value <0.01, and *** indicates that the P-value <0.001

Table 3 Network attributes of different water management cultivation treatment

处理 Treatment	节点数 Number of nodes	边数 Number of edges	正相关边数Number of positive correlation edges	负相关边数Number of negative correlation edges	聚类系数Clustering coefficient	模块性 Modularity
干旱管理	36	100	47	53	0.498	0.292
正常灌溉	50	100	49	51	0.403	0.444

Fig. 7 Network Diagram of various species at the genus level A: Drought management; B: normal irrigation. The sphere indicates the bacterial genus. The color of the sphere indicates the bacterial phylum. The size of the sphere indicates the average abundance of the bacterial genus. The line indicates that two bacterial genera are related. The thickness of the line indicates the strength of the correlation. Color of the connecting line: Red indicates positive correlation; green indicates negative correlation

References 30

[1]	黄孟雨, 刘志超, 谢新鑫, 等. 水旱栽培方式对山栏稻源库流特性的影响[J]. 南方农业学报, 2020, 51(4): 806-813.
	Huang MY, Liu ZC, Xie XX, et al. Effects of different flooding and drying cultivation methods on characteristics of source, sink and flow of Shanlan upland rice[J]. J South Agric, 2020, 51(4): 806-813.
[2]	刘华招, 季春德. 海南山栏稻种质资源的保护与利用[J]. 热带农业科学, 2016, 36(12): 49-51.
	Liu HZ, Ji CD. Conservation and utilization of Shanlan upland rice germplasm resources in Hainan Province[J]. Chin J Trop Agric, 2016, 36(12): 49-51.
[3]	黄昭奋, 黎瑞波, 麦全法, 等. 海南农业生物多样性与社会经济发展水平关系研究[J]. 热带农业科学, 2005, 25(2): 25-28.
	Huang ZF, Li RB, Mai QF, et al. The relationship between agrobidiversity and socially economic development in Hainan and its protective strategy[J]. Chin J Trop Agric, 2005, 25(2): 25-28.
[4]	吴丹, 吴川德, 何美丹, 等. 水作和旱作对山栏稻生长的影响[J]. 热带生物学报, 2017, 8(3): 318-323.
	Wu D, Wu CD, He MD, et al. The effects of paddy and upland cultivation on physiological parameters, agronomic traits and yield of shanlan upland rice[J]. J Trop Biol, 2017, 8(3): 318-323.
[5]	刘志超, 黄孟雨, 翟楠鑫, 等. 水旱两种栽培模式下海南山栏稻对白叶枯病抗性鉴定与评价[J]. 植物保护, 2021, 47(3): 191-199, 216.
	Liu ZC, Huang MY, Zhai NX, et al. Resistance evaluation and molecular identification of Hainan Shanlan upland rice to bacterial blight under flooding and drying cultivation conditions[J]. Plant Prot, 2021, 47(3): 191-199, 216.
[6]	柯智, 黄孟雨, 刘志超, 等. 栽培方式对山栏稻光合作用和产量的影响[J]. 热带生物学报, 2019, 10(4): 331-337, 438.
	Ke Z, Huang MY, Liu ZC, et al. Effects of cultivation patterns on photosynthesis, and yield and its components of shanlan upland rice[J]. J Trop Biol, 2019, 10(4): 331-337, 438.
[7]	何光亮. 不同栽培方式对山栏稻农艺性状和产量的影响[D]. 海口: 海南大学, 2018.
	He GL. Effects of different cultivation methods on agronomic traits and yield of shanlan upland rice[D]. Haikou: Hainan University, 2018.
[8]	Berendsen RL, Pieterse CMJ, Bakker PAHM. The rhizosphere microbiome and plant health[J]. Trends Plant Sci, 2012, 17(8): 478-486. doi: 10.1016/j.tplants.2012.04.001 pmid: 22564542
[9]	Edwards J, Johnson C, Santos-Medellín C, et al. Structure, variation, and assembly of the root-associated microbiomes of rice[J]. Proc Natl Acad Sci USA, 2015, 112(8): E911-E920.
[10]	Pang ZQ, Xu P, Yu DQ. Environmental adaptation of the root microbiome in two rice ecotypes[J]. Microbiol Res, 2020, 241: 126588. doi: 10.1016/j.micres.2020.126588 URL
[11]	Schmidt JE, Poret-Peterson A, Lowry CJ, et al. Has agricultural intensification impacted maize root traits and rhizosphere interactions related to organic N acquisition?[J]. AoB Plants, 2020, 12(4): plaa026. doi: 10.1093/aobpla/plaa026 URL
[12]	Qu Q, Zhang ZY, Peijnenburg WJGM, et al. Rhizosphere microbiome assembly and its impact on plant growth[J]. J Agric Food Chem, 2020, 68(18): 5024-5038. doi: 10.1021/acs.jafc.0c00073 URL
[13]	Shrestha PM, Kube M, Reinhardt R, et al. Transcriptional activity of paddy soil bacterial communities[J]. Environ Microbiol, 2009, 11(4): 960-970. doi: 10.1111/j.1462-2920.2008.01821.x pmid: 19170728
[14]	Gu YF, Zhang XP, Tu SH, et al. Soil microbial biomass, crop yields, and bacterial community structure as affected by long-term fertilizer treatments under wheat-rice cropping[J]. Eur J Soil Biol, 2009, 45(3): 239-246. doi: 10.1016/j.ejsobi.2009.02.005 URL
[15]	Bao XZ, Zou JX, Zhang B, et al. Arbuscular mycorrhizal fungi and microbes interaction in rice mycorrhizosphere[J]. Agronomy, 2022, 12(6): 1277. doi: 10.3390/agronomy12061277 URL
[16]	Doni F, Suhaimi NSM, Mispan MS, et al. Microbial contributions for rice production: from conventional crop management to the use of ‘omics’ technologies[J]. Int J Mol Sci, 2022, 23(2): 737. doi: 10.3390/ijms23020737 URL
[17]	Leng GY, Hall J. Crop yield sensitivity of global major agricultural countries to droughts and the projected changes in the future[J]. Sci Total Environ, 2019, 654: 811-821. doi: 10.1016/j.scitotenv.2018.10.434 URL
[18]	Khan A, Ding ZT, Ishaq M, et al. Applications of beneficial plant growth promoting rhizobacteria and mycorrhizae in rhizosphere and plant growth: a review[J]. Int J Agric Biol Eng, 2020, 13(5): 199-208.
[19]	Xiong JB, Lu JQ, Li XH, et al. Effect of rice(Oryza sativa L.)genotype on yield: evidence from recruiting spatially consistent rhizosphere microbiome[J]. Soil Biol Biochem, 2021, 161: 108395. doi: 10.1016/j.soilbio.2021.108395 URL
[20]	张静, 可文静, 刘娟, 等. 不同深度土壤控水对稻田土壤微生物区系及细菌群落多样性的影响[J]. 中国生态农业学报: 中英文, 2019, 27(2): 277-285.
	Zhang J, Ke WJ, Liu J, et al. Influence of water controlling depth on soil microflora and bacterial community diversity in paddy soil[J]. Chin J Eco Agric, 2019, 27(2): 277-285.
[21]	劳承英, 申章佑, 李艳英, 等. 基于高通量测序技术分析不同耕作方式下水稻根际土壤真菌多样性[J]. 热带作物学报, 2021, 42(9): 2717-2726. doi: 10.3969/j.issn.1000-2561.2021.09.038
	Lao CY, Shenzhang Y, Li YY, et al. Diversity analysis of fungal in rhizosphere soils of rice under different tillage methods based on high-throughput sequencing technique[J]. Chin J Trop Crops, 2021, 42(9): 2717-2726.
[22]	Xie ZC, Chu YK, Zhang WJ, et al. Bacillus pumilus alleviates drought stress and increases metabolite accumulation in Glycyrrhiza uralensis Fisch[J]. Environ Exp Bot, 2019, 158: 99-106. doi: 10.1016/j.envexpbot.2018.11.021 URL
[23]	Yin Y, Wang YF, Cui HL, et al. Distinctive structure and assembly of phyllosphere microbial communities between wild and cultivated rice[J]. Microbiol Spectr, 2023, 11(1): e0437122. doi: 10.1128/spectrum.04371-22 URL
[24]	Cheng HY, Yuan MS, Tang L, et al. Integrated microbiology and metabolomics analysis reveal responses of soil microorganisms and metabolic functions to phosphorus fertilizer on semiarid farm[J]. Sci Total Environ, 2022, 817: 152878. doi: 10.1016/j.scitotenv.2021.152878 URL
[25]	Zhu JY, Li A, Zhang J, et al. Effects of nitrogen application after abrupt drought-flood alternation on rice root nitrogen uptake and rhizosphere soil microbial diversity[J]. Environ Exp Bot, 2022, 201: 105007. doi: 10.1016/j.envexpbot.2022.105007 URL
[26]	Jang SW, Yoou MH, Hong WJ, et al. Re-analysis of 16S amplicon sequencing data reveals soil microbial population shifts in rice fields under drought condition[J]. Rice, 2020, 13(1): 44. doi: 10.1186/s12284-020-00403-6
[27]	Zhou GX, Xu XF, Qiu XW, et al. Biochar influences the succession of microbial communities and the metabolic functions during rice straw composting with pig manure[J]. Bioresour Technol, 2019, 272: 10-18. doi: 10.1016/j.biortech.2018.09.135 URL
[28]	Kanasugi M, Sarkodee-Addo E, Ansong Omari R, et al. Exploring rice root microbiome; the variation, specialization and interaction of bacteria and fungi in six tropic savanna regions in Ghana[J]. Sustainability, 2020, 12(14): 5835. doi: 10.3390/su12145835 URL
[29]	Zhang JY, Liu YX, Zhang N, et al. NRT1.1B is associated with root microbiota composition and nitrogen use in field-grown rice[J]. Nat Biotechnol, 2019, 37(6): 676-684. doi: 10.1038/s41587-019-0104-4 pmid: 31036930
[30]	刘文静, 张建伟, 邱崇文, 等. 水旱轮作对土壤微生物群落构建过程的影响机制[J]. 土壤, 2020, 52(4): 710-717.
	Liu WJ, Zhang JW, Qiu CW, et al. Study on community assembly processes under paddy-upland rotation[J]. Soils, 2020, 52(4): 710-717.