生防菌NCD-2菌株定量检测体系的建立及其在棉花根际定植检测中的应用

doi:10.11963/cs20210062

棉花学报 ›› 2022, Vol. 34 ›› Issue (2): 162-172.doi: 10.11963/cs20210062

• 研究与进展 • 上一篇

生防菌NCD-2菌株定量检测体系的建立及其在棉花根际定植检测中的应用

苏星^1，²()，苏振贺²，宣立锋³，李社增²，王培培²，郭庆港²，马平^2，^*()

1.河北农业大学植物保护学院,河北保定071000
2.河北省农林科学院植物保护研究所/河北省农业有害生物综合治理中心/农业农村部华北北部作物有害生物综合治理重点实验室,河北保定 071000
3.河北省农林科学院石家庄果树研究所,石家庄 050061

收稿日期:2021-10-28 出版日期:2022-03-15 发布日期:2022-05-30
通讯作者: 马平 E-mail:pingma88@126.com
作者简介:苏星（1999―）,女,硕士, suxing66882021@163.com
基金资助:
国家现代农业产业技术体系——棉花产业技术体系(CARS-15-19);河北省重点研发计划(19226510D);国家自然科学基金(32172487);河北省农林科学院现代农业科技创新工程(2022KJCXZX-ZBS-1)

Development of quantitative detection system for biocontrol strain NCD-2 and its application in rhizosphere colonization of cotton

Su Xing^1,²(), Su Zhenhe², Xuan Lifeng³, Li Shezeng², Wang Peipei², Guo Qinggang², Ma Ping^2,^*()

1. College of Plant Protection, Agricultural University of Hebei, Baoding, Hebei 071000, China
2. Institute of Plant Protection, Hebei Academy of Agriculture and Forestry Sciences/Integrated Pest Management Center of Hebei Province/Key Laboratory of IPM on Crops in Northern Region of North China, Ministry of Agriculture and Rural Affairs,Baoding, Hebei 071000, China
3. Shijiazhuang Institute of Fruit Trees, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang 050061, China

Received:2021-10-28 Online:2022-03-15 Published:2022-05-30
Contact: Ma Ping E-mail:pingma88@126.com

摘要/Abstract

摘要：

【目的】建立生防枯草芽孢杆菌NCD-2菌株的定量检测体系,明确生防菌在棉花根际土壤中的定植情况。【方法】根据NCD-2菌株全基因组序列设计特异性引物;利用聚合酶链式反应（polymerase chain reaction, PCR）技术,构建NCD-2菌株的实时PCR检测体系,并检测NCD-2菌株在棉花根际的定植情况。【结果】所构建的NCD-2菌株实时PCR检测体系能够特异性地定量检测土壤中NCD-2菌株的数量。用有效活菌数10⁹ mL^-1的NCD-2菌液处理棉种,在灭菌土中播种后8 d和16 d,用实时PCR检测其在棉花根际土壤中的定植数量分别为1.14×10⁵ g^-1和9.5×10⁴ g^-1,与传统计数法检测的结果（2.15×10⁵ g^-1和2.45×10⁵ g^-1）高度相关,2种方法结果的相关系数在播种后8 d时为0.99,在播种后16 d时为0.95。而将NCD-2菌株处理后的棉种播种于含有立枯丝核菌的土壤中后16 d,用实时PCR检测其在根际土壤中的定植数量为7.6×10⁵ g^-1,此时NCD-2菌株对棉花立枯病防治效果达到67.9%。【结论】所构建的实时PCR检测体系能够准确检测NCD-2菌株在根际土壤中的定植情况,为高效使用NCD-2菌株防控病害奠定了基础。

关键词: 枯草芽孢杆菌; 定量检测; 根际; 实时聚合酶链式反应; 棉花

Abstract:

[Objective] A quantitative detection technique for biocontrol Bacillus subtilis NCD-2 was developed and used to evaluate the colonization of strain NCD-2 in cotton rhizosphere. [Method] Specific primers for strain NCD-2 were designed based on the whole genome sequences of strain NCD-2. The colonization dynamics of strain NCD-2 in cotton rhizosphere soil were quantified by real-time polymerase chain reaction (PCR). [Result] The real-time PCR detection technique for strain NCD-2 was successfully developed. Real-time PCR detection result showed that the population contents of strain NCD-2 in cotton rhizosphere soil were 1.14×10⁵ g^-1 and 9.5×10⁴ g^-1 on the 8^th day and 16^th day after sowing, respectively. Comparatively, 2.15×10⁵ g^-1 and 2.45×10⁵ g^-1 of strain NCD-2 in soil at the 8^th day and the 16^th day after sowing were obtained by traditional colony counting method. The correlation coefficients between the two methods were 0.99 at the 8^th day and 0.95 at the 16^th day. The control effect of NCD-2 strains against cotton rhizoctonia damping-off was 67.9% at 16 days after seed treatment. At that time the population content of strain NCD-2 was 7.6×10⁵ g^-1 in soil with real-time PCR detection. [Conclusion] The established real-time PCR detection technique in this study can accurately reflect the colonization of NCD-2 strain in cotton rhizosphere, and lays a foundation for using the strain to effectively control diseases.

Key words: Bacillus subtilis; quantification; rhizosphere; real-time polymerase chain reaction; cotton

苏星, 苏振贺, 宣立锋, 李社增, 王培培, 郭庆港, 马平. 生防菌NCD-2菌株定量检测体系的建立及其在棉花根际定植检测中的应用[J]. 棉花学报, 2022, 34(2): 162-172.

Su Xing, Su Zhenhe, Xuan Lifeng, Li Shezeng, Wang Peipei, Guo Qinggang, Ma Ping. Development of quantitative detection system for biocontrol strain NCD-2 and its application in rhizosphere colonization of cotton[J]. Cotton Science, 2022, 34(2): 162-172.

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参考文献 31

[1]	Montesinos E. Development, registration and commercialization of microbial pesticides for plant protection[J/OL]. International Microbiology, 2003, 6(4): 245-252 [2021-10-27]. https://doi.org/10.1007/s10123-003-0144-x.
[2]	Niu B, Wang W, Yuan Z, et al. Microbial interactions within multiple-strain biological control agents impact soil-borne plant disease[J/OL]. Frontiers in Microbiology, 2020, 11: 585404 [2021-10-27]. https://doi.org/10.3389/fmicb.2020.585404.
[3]	Pérez-García A, Romero D, de Vicente A, et al. Plant protection and growth stimulation by microorganisms: biotechnological applications of Bacilli in agriculture[J/OL]. Current Opinion in Biotechnology, 2011(4): 187-193[2021-10-27]. https://doi.org/10.1016/j.copbio.2010.12.003.
[4]	Sivasakthi S, Usharani G, Saranraj P. Biocontrol potentiality of plant growth promoting bacteria(PGPR)-Pseudomonas fluorescens and Bacillus subtilis: a review[J/OL]. African Journal of Microbiology Research, 2014, 9(16): 1265-1277 [2021-10-27]. https://doi.org/10.5897/AJAR2013.7914.
[5]	Saraf M, Pandya U, Thakkar A. Role of allelochemicals in plant growth promoting rhizobacteria for biocontrol of phytopathogens[J/OL]. Microbiological Research, 2014, 169(1): 18-29 [2021-10-27]. https://doi.org/10.1016/j.micres.2013.08.009.
[6]	Shyam K, Pierre J, Sharon D. Bacterial endophyte colonization and distribution within plants[J/OL]. Microorganisms, 2017, 5(4): 77[2021-10-27]. https://doi.org/10.3390/microorganisms5040077.
[7]	Blake C, Christensen M N, Kovács T. Molecular aspects of plant growth promotion and protection by Bacillus subtilis[J/OL]. Molecular Plant-Microbe Interactions, 2021, 34(1): 15-25 [2021-10-27]. https://doi.org/10.1094/MPMI-08-20-0225-CR.
[8]	Cho I H, Irudayaraj J. In-situ immuno-gold nanoparticle network ELISA biosensors for pathogen detection[J/OL]. International Journal of Food Microbiology, 2013, 164(1): 70-75 [2021-10-27]. https://doi.org/10.1016/j.ijfoodmicro.2013.02.025.
[9]	Badosa E, Moreno C, Montesinos E. Lack of detection of ampicillin resistance gene transfer from Bt176 transgenic corn to culturable bacteria under field conditions[J/OL]. FEMS Microbiology Ecology, 2004, 48(2): 169-178 [2021-10-27]. https://doi.org/10.1016/j.femsec.2004.01.005.
[10]	Zhen B, Li J Y, Guo Y B, et al. A plating-PCR technique for detection and quantification of the biological control agent Agrobacterium vitis strain E26 in soil under controlled conditions[J/OL]. Journal of Phytopathology, 2012, 160(9): 496-499 [2021-10-27]. https://doi.org/10.1111/j.1439-0434.2012.01929.x.
[11]	Gharbi Y, Barkallah M, Bouazizi E, et al. Development and validation of a new real-time assay for the quantification of Verticillium dahliae in the soil: a comparison with conventional soil plating[J/OL]. Mycological Progress, 2016, 15(6): 1-13 [2021-10-27]. https://doi.org/10.1007/s11557-016-1196-6.
[12]	张冬冬, 刘涛, 高同国, 等. 棉花黄萎病拮抗细菌Z-5菌株的定殖能力检测[J/OL]. 棉花学报, 2013, 25(6):510-516 [2021-10-27]. https://doi.org/10.3969/j.issn.1002-7807.2013.06.006.
	Zhang Dongdong, Liu Tao, Gao Tongguo, et al. Detection of the colonization ability of antagonistic bacteria strain Z-5 against cotton Verticillium wilt[J/OL]. Cotton Science, 2013, 25(6): 510-516[2021-10-27]. https://doi.org/10.3969/j.issn.1002-7807.2013.06.006.
[13]	Kim T G, Knudsen G R. Comparison of plate count microscopy, and DNA quantification methods to quantify a biocontrol fungus[J/OL]. Applied Soil Ecology, 2016, 98: 285-288 [2021-10-27]. https://doi.org/10.1016/j.apsoil.2015.10.010.
[14]	程承, 李石力, 刘颖, 等. 试验土壤中烟草青枯病菌的RT-qPCR检测分析[J/OL]. 烟草科技, 2017, 50(1): 12-16[2021-10-27]. https://doi.org/10.16135/j.issn1002-0861.2015.0668.
	Li Shili, Liu Ying, et al. RT-qPCR detection and quantitative analysis of Ralstonia solanacearum in soil[J/OL]. Tobacco Science & Technology, 2017, 50(1): 12-16[2021-10-27]. https://doi.org/10.16135/j.issn1002-0861.2015.0668.
[15]	王川, 董莉, 邱慧珍, 等. 马铃薯立枯丝核菌拮抗菌QHZ11的实时荧光定量PCR快速检测与应用[J/OL]. 微生物学通报, 2020, 47(12): 393-403[2021-10-27]. https://doi.org/10.13344/j.microbiol.china.200100.
	Wang Chuan, Dong Li, Qiu Huizhen, et al. Rapid detection and application of antagonistic bacterium QHZ11 against Rhizoctonia solani in potato by real-time fluorescence quantitative PCR[J/OL]. Microbiology China, 2020, 47(12): 393-403 [2021-10-27]. https://doi.org/10.13344/j.microbiol.china.200100.
[16]	Sa R B, Zhang J L, Sun J Z, et al. Colonization characteristics of poplar fungal disease biocontrol bacteria N6-34 and the inhibitory effect on pathogenic fungi by real-time fluorescence quantitative PCR detection[J/OL]. Current Microbiology, 2021, 78: 2916-2925 [2021-10-27]. https://doi.org/10.1007/s00284-021-02529-2.
[17]	李社增, 鹿秀云, 马平, 等. 防治棉花黄萎病的生防细菌NCD-2的田间效果评价及其鉴定[J]. 植物病理学报, 2005, 35(5): 451-455.
	Li Shezeng, Lu Xiuyun, Ma Ping, et al. Evaluation of biocontrol potential of a bacterial strain NCD-2 against cotton Verticillium wilt in field trials[J]. Acta Phytopathologica Sinica, 2005, 35(5): 451-455.
[18]	Guo S, Zhang J W, Dong L H, et al. Fengycin produced by Bacillus subtilis NCD-2 is involved in suppression of clubroot on Chinese cabbage[J/OL]. Biological Control, 2019, 136: 104001 [2021-10-27]. https://doi.org/10.1016/j.biocontrol.2019.104001.
[19]	Savazzini F, Longa C, Pertot I, et al. Real-time PCR for detection and quantification of the biocontrol agent Trichoderma atroviride strain SC1 in soil[J/OL]. Journal of Microbiological Methods, 2008, 73(2): 185-194[2021-10-27]. https://doi.org/10.1016/j.mimet.2008.02.004.
[20]	Manyi-Loh C, Mamphweli S, Meyer E, et al. Antibiotic use in agriculture and its consequential resistance in environmental sources: potential public health implications[J/OL]. Molecules, 2018, 23(4): 795[2021-10-27]. https://doi.org/10.3390/molecules23040795.
[21]	Compeau G B, Al-Achi B J, Platsouka E, et al. Survival of rifampin-resistant mutants of Pseudomonas fluorescens and Pseudomonas putida in soil system[J/OL]. Applied and Environmental Microbiology, 1988, 54(10): 2432-2438 [2021-10-27]. https://doi.org/10.1128/AEM.54.10.2432-2438.1988.
[22]	Wang J, Jacobs J L, Byrne J M, et al. Improved diagnoses and quantification of Fusarium virguliforme, causal agent of soybean sudden death syndrome[J/OL]. Phytopathology, 2015, 105(3): 378-387 [2021-10-27]. https://doi.org/10.1094/PHYTO-06-14-0177-R.
[23]	Knudsen G R, Kim T G, Bae Y S, et al. Use of quantitative real-time PCR to unravel ecological complexity in a biological control system[J/OL]. Advances in Bioscience & Biotechnology, 2015, 6(4): 237-244 [2021-10-27]. https://doi.org/10.4236/abb.2015.64023.
[24]	Noris E, Miozzi L. Real-time PCR protocols for the quantification of the Begomovirus Tomato Yellow Leaf Curl Sardinia Virus in tomato plants and in its insect vector[M/OL]// UyedaI, MasutaC. Plant virology protocols. New York: Humana Press, 2014: 61-72 [2021-10-27]. https://doi.org/10.1007/978-1-4939-1743-3_6.
[25]	Johansson A H, Bejai S, Niazi A, et al. Studies of plant colonisation by closely related Bacillus amyloliquefaciens biocontrol agents using strain specific quantitative PCR assays[J/OL]. Antonie van Leeuwenhoek, 2014, 106(6): 1247-1257[2021-10-27]. https://doi.org/10.1007/s10482-014-0295-0.
[26]	Zhang Y, Wang X, Pang G, et al. Two-step genomic sequence comparison strategy to design trichoderma strain-specific primers for quantitative PCR[J/OL]. AMB Express, 2019, 9: 179[2021-10-27]. https://doi.org/10.1186/s13568-019-0904-4.
[27]	Case R J, Boucher Y, Dahllof I, et al. Use of 16S rRNA and rpoB genes as molecular markers for microbial ecology studies[J/OL]. Applied and Environmental Microbiology, 2007, 73(1): 278-288 [2021-10-27]. https://doi.org/10.1128/AEM.01177-06.
[28]	Schrader C, Schielke A, Ellerbroek L, et al. PCR inhibitors-occurrence, properties and removal[J/OL]. Journal of Applied Microbiology, 2012, 113(5): 1014-1026 [2021-10-27]. https://doi.org/10.1111/j.1365-2672.2012.05384.x.
[29]	Opel K L, Chung D, Mccord B R. A study of PCR inhibition mechanisms using real time PCR[J/OL]. Journal of Forensic Sciences, 2010, 55(1): 25-33 [2021-10-27]. https://doi.org/10.1111/j.1556-4029.2009.01245.x.
[30]	任海英, 戚行江, 梁森苗, 等. 利用常规PCR和实时荧光定量PCR检测杨梅凋萎病菌[J/OL]. 植物病理学报, 2016, 46(1): 1-10 [2021-10-27]. https://doi.org/10.13926/j.cnki.apps.2016.01.001.
	Ren Haiying, Qi Xingjiang, Liang Senmiao, et al. Use of conventional and real-time quantitative PCR to detect Pestalotiopsis, the cause of bayberry twig blight[J/OL]. Acta Phytopathology Sinica, 2016, 46(1): 1-10[2021-10-27]. https://doi.org/10.13926/j.cnki.apps.2016.01.001.
[31]	Samaras A, Nikolaidis M, Antequera-Gómez M L, et al. Whole genome sequencing and root colonization studies reveal novel insights in the biocontrol potential and growth promotion by Bacillus subtilis MBI 600 on cucumber[J/OL]. Frontiers in Microbiology, 2021, 11:600393[2021-10-27]. https://doi.org/10.3389/fmicb.2020.600393.

菌株名称 Strains name	菌株分类 Species	来源 Source	登录号 GenBank accession no.
NCD-2	B. subtilis	Lab stock	CP023755.1
168	B. subtilis	BGSC	NC_000964.3
BSn5	B. subtilis	-	NC_014976.1
RO-NN-1	B. subtilis	-	NC_017195
MAS88	B. subtilis	BGSC
ATCC21332	B. subtilis	BGSC
NDH03	B. subtilis	BGSC
BD170	B. subtilis	BGSC
pY143	B. subtilis	CAU
ISW1214	B. subtilis	TaKaRa
W23	B. subtilis subsp. spizizenii	-	NC_014479
TU-B-10	B. subtilis subsp. spizizenii	-	NC_016047
RO-C-2	B. mojavensis	UCLA
CU8004	B. amyloliquefaciens	BGSC
FZB42	B. velezensis	BGSC	NC_009725
DSM7	B. amyloliquefaciens	-	NC_014551
1942	B. atrophaeus	-	NC_014639
SB512	B. atrophaeus	BGSC
NRS-213T	B. atrophaeus	BGSC
ATCC8480	B. licheniformis	BGSC
ATCC11946	B. licheniformis	BGSC
ATCC14580	B. licheniformis	-	NC_006322
ATCC7061	B. pumilus	BGSC
Biosubtyl	B. pumilus	BGSC
SAFR-032	B. pumilus	-	NC_009848
899	B. megaterium	BGSC
ATCC14581	B. megaterium	BGSC
ATCC10792	B. thuringiensis	-	NZ_CM000753
HD2	B. thuringiensis	BGSC
T01246	B. thuringiensis	BGSC
NRS854	B. firmus	BGSC
NRS613	B. firmus	BGSC

菌株名称 Strains	来源 Source	GenBank登录号GenBank accession No.
菌株名称 Strains	来源 Source	phoR	gyrB	16S rDNA
70A-7	Lab stock	JN580923	JQ916067	GU269571
BDT-14	Lab stock	JN580935	JQ916072	GU269574
BZT-34	Lab stock	JN580929	JQ769378	GU269577
CJT-2	Lab stock	JN580931	JQ769379	GU269578
DHT-12	Lab stock	JN580932	JQ916074	GU269579
DHT-13	Lab stock	JN580933	JQ916075	GU269580
DHT-27	Lab stock	JN580944	JQ916076	GU269581
DHT-33	Lab stock	JN580936	JQ916077	GU269582
LBT-338	Lab stock	JN580934	JQ916078	GU269611
NZT-14-84	Lab stock	JN580963	JQ916081	GU269614
BAB-1	Lab stock	JQ916089	JQ916082	JQ916087
CAB-1	Lab stock	JN580930	JQ361766	JN571112
XJT-7	Lab stock	JN580926	JQ769380	GU269615
NZT-59	Lab stock	JN580965	JQ916079	GU269617
BDT-26	Lab stock	JN580928	JQ916073	GU269619
HMB6313	Lab stock	JN580945	JQ916069	GU269597
HMB6336	Lab stock	JN580962	JQ916068	GU269601
HMB15054	Lab stock	JN580967	JQ916070	-
HMB19198	Lab stock	JN580968	JQ916071	-
HMB20199	Lab stock	JN580969	JQ916083	-
HMB22277	Lab stock	JQ916088	JQ916084	JQ916086
Y2	Lab stock	JN580941	JQ916080	-

处理 Treatment	土壤立枯丝核菌含量 Content of Rhizoctonia solani in soil/(g^-1)	土壤NCD-2菌株含量 Content of NCD-2 strains in soil/(10⁵ g^-1)	防治效果 Control effect/%
CK	3 011±138	0.0	0.0
NCD-2	416±59	7.6±1.9	67.9

生防菌NCD-2菌株定量检测体系的建立及其在棉花根际定植检测中的应用

Development of quantitative detection system for biocontrol strain NCD-2 and its application in rhizosphere colonization of cotton

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