枯草芽孢杆菌NCD-2对棉花根系分泌物L-脯氨酸响应的转录-蛋白质组学联合分析

doi:10.3864/j.issn.0578-1752.2021.21.009

Abstract

Abstract:

【Objective】L-proline in root exudates of cotton is one of the key factors affecting the colonization of biocontrol microorganisms. Previous studies showed that L-proline could improve the ability of Bacillus subtilis NCD-2 biofilm formation. The objective of this study is to explore the regulatory genes related to the biofilm formation and biocontrol potential of strain NCD-2 through high-throughput sequencing technology, and to lay a foundation for further understanding the molecular interaction between cotton root exudates and biocontrol strain.【Method】Strain NCD-2 was co-cultured with L-proline at the concentration of 10 mg·mL ^-1 for 24 h, and it was analyzed by transcriptome (RNA-seq) and isotope labeled relative quantitative proteomics (iTRAQ). The expression of some differential genes in different metabolic pathways was verified by RT-qPCR.【Result】Transcriptome analysis showed that 1 071 differentially expressed genes (DEGs) were obtained after L-proline and NCD-2 co-culture, of which 602 genes were up-regulated and 469 genes were down-regulated. GO analysis showed that 49, 14 and 30 functional items were significantly enriched in biological process, cell component and molecular function, respectively. KEGG pathways were mainly enriched in compound metabolism, flagellum assembly, bacterial motility or chemotaxis. Proteomic analysis showed that a total of 211 differentially expressed proteins (DEPs) were detected compared to the control, of which 118 proteins were up-regulated and 93 proteins were down-regulated. GO analysis showed that 13 and 8 functional items were significantly enriched in biological process and molecular function, respectively. KEGG pathways were mainly enriched in amino acid metabolism, carbohydrate metabolism, flagellum assembly and ABC transporter. Further transcriptional-proteomics analysis revealed that 112 DEGs (or DEPs), including 38 down-regulated genes (or proteins) and 74 up-regulated genes (or proteins), were detected. GO functional items were significantly enriched in nine aspects, including nutrient reservoir activity, catalytic activity, cell membrane, localization, cellular lipid metabolic process, oxidation-reduction process, sigma factor activity, transport activity and spore formation. KEGG pathways were mainly enriched in energy metabolism, ABC transporter, antibiotic biosynthesis, flagellum assembly, motility or chemotaxis and two-component system. Twenty-six DEGs were verified by RT-qPCR. The results showed that there were some differences in the expression level, but the expression trend was basically consistent with that of RNA-seq and iTRAQ.【Conclusion】The interaction between L-proline in cotton root exudates and B. subtilis NCD-2 is a complex biological process, which depends on multiple genes in different metabolic pathway networks. It is cleared that DEGs (or DEPs) of the two-component system, antibiotic biosynthesis, energy metabolism, motility or chemotaxis, flagellum assembly and ABC transporter pathway may play an important role in the interaction between cotton root exudates and B. subtilis.

Key words: L-proline, Bacillus subtilis, transcriptome, proteome, interaction relationship

ZHAO WeiSong,GUO QingGang,DONG LiHong,WANG PeiPei,SU ZhenHe,ZHANG XiaoYun,LU XiuYun,LI SheZeng,MA Ping. Transcriptome and Proteome Analysis of Bacillus subtilis NCD-2 Response to L-proline from Cotton Root Exudates[J].Scientia Agricultura Sinica, 2021, 54(21): 4585-4600.

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References 44

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基因 Gene		序列Sequence (5′ to 3′)	基因 Gene		序列Sequence (5′ to 3′)
fliF	F	ACCGAAAGCGGGAACTAC	opuCC	F	GCAAGGAAGCGGAGAAAG
fliF	R	CATCAGGCGGCTCTACCA	opuCC	R	AGCCGTAGGAATCAAACCA
gInQ	F	TATCGGGATGGTGTTTCA	gcvPB	F	TTATTTCCCGCTTAATGTTG
gInQ	R	GTCAGCCTTGTCTGGGAT	gcvPB	R	TCTTCCGCCTCGTATCTG
cheY	F	GGAGCACAAGCGGTAGAG	putC	F	AATCGTTTCAATCAACCCAG
cheY	R	CTGAATGGCATCAATAAC	putC	R	TATCGGCATCCGCCTCGT
fliY	F	CAGACCGTATTCCTGATG	rocA	F	TAGTTGAGCATCCGAAGAC
fliY	R	CACCGTTTCTTCTTCCTC	rocA	R	CAATTACCCGTTTGAGCC
opuCA	F	CCAGCAGAACATCTCACTC	yodQ	F	GGCAATACAGCCCTTCTT
opuCA	R	GCGGATAACGGTCTAAATAC	yodQ	R	GCCGCACTCTTCATCTAC
znuA	F	GGGCTTTCACCTGACCAA	ald	F	CCTCTTCTGACGCCAATG
znuA	R	CGAGCGTATCTGCGACCT	ald	R	CAACGCCTCCTCCGATAA
gapB	F	AAGAGGTTGTGGCTGGTG	yerA	F	GAGAAGGCTGGAACTGGG
gapB	R	TTGCTTCGACGACTATGT	yerA	R	ATTGTAGGCGTCGATTGC
mmgD	F	AATGGAAACGCTGGAACG	asnO	F	TGTCGGATGTGCCTGTTT
mmgD	R	TGTTTGCGGAAGGAGACC	asnO	R	CATTTGTGGTGCGTTGTG
acoC	F	TGGACCAGGCGGACGAAT	yisZ	F	AGGATCGGGACATGGTTA
acoC	R	TCGGGCAGCGATGACCTT	yisZ	R	ATGAAATCGGGTGAAAGC
thrD	F	ACTGATCGCCGCTTACTT	ggt	F	ACACTGTCCAGGATTTCG
thrD	R	ACCGCTCCGTGAGAATGT	ggt	R	GGAGGAGGAGTAGTAGCG
yjmD	F	CAGCGGAGGTGAAGAAGC	yoaD	F	CCCGAACTTTCATTTGTC
yjmD	R	GAGGGTAGCGAGCGGATT	yoaD	R	CTCCATCCTTCAGCCACT
epsA	F	TCGAATCTCAGTGACATCCA	epsC	F	AATCCAGAAGAGGCGGTCAA
epsA	R	AGATAGGTGCAATTCCGC	epsC	R	GCCGAAGCGAACAGCAAC
ssuB	F	ATTATCAATCGCACCAGG	scoB	F	TTGTCGCAAATGAGATACCC
ssuB	R	CAACAGTCAGCCAAGGAA	scoB	R	CGTCTTCCGTTCCTTCCA
gyrB	F	GAAGCACGGACAATCACC
gyrB	R	TCCAAAGCACTCTTACGG

处理 Treatment	原始序列 Raw reads	过滤序列 Clean reads	过滤序列大小 Clean reads bases (G)	Q20 比例Q20 percentage (%)	Q30比例Q30 percentage (%)	G和C占总碱基数量百分比 GC content (%)
CK	11104298±1620312	10870077±1617999	1.63±0.24	97.46±0.11	92.90±0.32	41.81±0.40
T	8978376±1390913	8783987±1431917	1.32±0.22	97.99±0.11	93.79±0.27	43.30±0.05

项目 Item	处理 Treatment	FPKM值 FPKM value
项目 Item	处理 Treatment	0-1	1-3	3-15	15-60	>60
基因数量 Number of genes	CK	616.33±7.64	130.33±10.41	493.67±31.13	984.67±33.01	2305.00±54.44
基因数量 Number of genes	T	690.00±22.27	165.67±4.73	569.33±18.58	1073.67±36.23	2031.33±74.22
基因表达比例 Gene expression ratio (%)	CK	13.60±0.17	2.87±0.23	10.90±0.69	21.74±0.73	50.88±1.20
基因表达比例 Gene expression ratio (%)	T	15.23±0.49	3.66±0.10	12.57±0.41	23.70±0.80	44.84±1.64

KEGG代谢途径 KEGG pathway	差异基因数目 Number of DEGs	所有基因数目 Number of all genes	差异表达基因比例 DEGs ratio (%)	P值 P-value	表达调控 Regulated
不同环境的微生物代谢 Microbial metabolism in diverse environments	40	169	23.67	0.0076	Up
链霉素生物合成 Streptomycin biosynthesis	6	9	66.67	0.0088	Up
碳代谢Carbon metabolism	25	94	26.60	0.0103	Up
硫代谢Sulfur metabolism	8	17	47.06	0.0118	Up
乙醛酸和二羧酸代谢 Glyoxylate and dicarboxylate metabolism	9	25	36.00	0.0276	Up
鞭毛组装 Flagellar assembly	26	33	78.79	0	Down
细菌趋化性 Bacterial chemotaxis	13	24	54.17	0	Down
核糖体 Ribosome	18	88	20.45	0.0248	Down
萜类化合物生物合成 Terpenoid backbone biosynthesis	5	14	35.71	0.0413	Down
错配修复Mismatch repair	6	20	30.00	0.0475	Down

KEGG代谢途径 KEGG pathway	注释代谢途径的差异表达蛋白数量 Number of DEPs with pathway annotation	注释代谢途径的蛋白数量 Number of proteins with pathway annotation	差异蛋白比例 DEPs ratio (%)	P值 P-value	上调数量Up-regulated number	下调数量Down-regulated number
酮体的合成与降解 Synthesis and degradation of ketone bodies	4	5	80.00	0.0004	4	0
乙醛酸和二羧酸代谢 Glyoxylate and dicarboxylate metabolism	9	29	31.03	0.0009	7	2
牛磺酸和亚牛磺酸代谢 Taurine and hypotaurine metabolism	3	7	42.86	0.0224	2	1
丙氨酸、天冬氨酸和谷氨酸代谢 Alanine, aspartate and glutamate metabolism	7	31	22.58	0.0226	4	3
鞭毛组装Flagellar assembly	2	3	66.67	0.0255	0	2
戊糖和葡萄糖醛酸的相互转化 Pentose and glucuronate interconversions	5	19	26.32	0.0284	4	1
精氨酸和脯氨酸代谢 Arginine and proline metabolism	5	19	26.32	0.0284	3	2
丁酸代谢Butanoate metabolism	5	19	26.32	0.0284	5	0
不同环境的微生物代谢 Microbial metabolism in diverse environments	22	151	14.57	0.0335	13	9
ABC转运蛋白ABC transporter	13	79	16.46	0.0486	7	6

Transcriptome and Proteome Analysis of Bacillus subtilis NCD-2 Response to L-proline from Cotton Root Exudates

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[3]	SUN BaoJuan,WANG Rui,SUN GuangWen,WANG YiKui,LI Tao,GONG Chao,HENG Zhou,YOU Qian,LI ZhiLiang. Transcriptome and Metabolome Integrated Analysis of Epistatic Genetics Effects on Eggplant Peel Color [J]. Scientia Agricultura Sinica, 2022, 55(20): 3997-4010.
[4]	LIU Xin,ZHANG YaHong,YUAN Miao,DANG ShiZhuo,ZHOU Juan. Transcriptome Analysis During Flower Bud Differentiation of Red Globe Grape [J]. Scientia Agricultura Sinica, 2022, 55(20): 4020-4035.
[5]	WANG RongHua,MENG LiFeng,FENG Mao,FANG Yu,WEI QiaoHong,MA BeiBei,ZHONG WeiLai,LI JianKe. Proteome Analysis of the Salivary Gland of Nurse Bee from High Royal Jelly Producing Bees and Italian Bees [J]. Scientia Agricultura Sinica, 2022, 55(13): 2667-2684.
[6]	GUO YongChun, WANG PengJie, JIN Shan, HOU Binghao, WANG ShuYan, ZHAO Feng, YE NaiXing. Identification of Co-Expression Gene Related to Tea Plant Response to Glyphosate Based on WGCNA [J]. Scientia Agricultura Sinica, 2022, 55(1): 152-166.
[7]	HuaZhi CHEN,YuanChan FAN,HaiBin JIANG,Jie WANG,XiaoXue FAN,ZhiWei ZHU,Qi LONG,ZongBing CAI,YanZhen ZHENG,ZhongMin FU,GuoJun XU,DaFu CHEN,Rui GUO. Improvement of Nosema ceranae Genome Annotation Based on Nanopore Full-Length Transcriptome Data [J]. Scientia Agricultura Sinica, 2021, 54(6): 1288-1300.
[8]	DU Yu,ZHU ZhiWei,WANG Jie,WANG XiuNa,JIANG HaiBin,FAN YuanChan,FAN XiaoXue,CHEN HuaZhi,LONG Qi,CAI ZongBing,XIONG CuiLing,ZHENG YanZhen,FU ZhongMin,CHEN DaFu,GUO Rui. Construction and Annotation of Ascosphaera apis Full-Length Transcriptome Utilizing Nanopore Third-Generation Long-Read Sequencing Technology [J]. Scientia Agricultura Sinica, 2021, 54(4): 864-876.
[9]	HOU ChengLi,HUANG CaiYan,ZHENG XiaoChun,LIU WeiHua,YANG Qi,ZHANG DeQuan. Changes of Antioxidant Activity and Its Possible Mechanism in Tan Sheep Meat in Different Postmortem Time [J]. Scientia Agricultura Sinica, 2021, 54(23): 5110-5124.
[10]	SHAO MeiQi,ZHAO WeiSong,SU ZhenHe,DONG LiHong,GUO QingGang,MA Ping. Effect of Bacillus subtilis NCD-2 on the Growth of Tomato and the Microbial Community Structure of Rhizosphere Soil Under Salt Stress [J]. Scientia Agricultura Sinica, 2021, 54(21): 4573-4584.
[11]	LIU Lian,TANG ZhiPeng,LI FeiFei,XIONG Jiang,LÜ BiWen,MA XiaoChuan,TANG ChaoLan,LI ZeHang,ZHOU Tie,SHENG Ling,LU XiaoPeng. Fruit Quality in Storage, Storability and Peel Transcriptome Analysis of Rong’an Kumquat, Huapi Kumquat and Cuimi Kumquat [J]. Scientia Agricultura Sinica, 2021, 54(20): 4421-4433.
[12]	LIN Bing,CHEN YiQuan,ZHONG HuaiQin,YE XiuXian,FAN RongHui. Analysis of Key Genes About Flower Color Variation in Iris hollandica [J]. Scientia Agricultura Sinica, 2021, 54(12): 2644-2652.
[13]	QIN QiuHong,HE XuJiang,JIANG WuJun,WANG ZiLong,ZENG ZhiJiang. The Capping Pheromone Contents and Putative Biosynthetic Pathways in Larvae of Honeybees Apis cernana [J]. Scientia Agricultura Sinica, 2021, 54(11): 2464-2475.
[14]	LONG Qin,DU MeiXia,LONG JunHong,HE YongRui,ZOU XiuPing,CHEN ShanChun. Effect of Transcription Factor CsWRKY61 on Citrus Bacterial Canker Resistance [J]. Scientia Agricultura Sinica, 2020, 53(8): 1556-1571.
[15]	CaiLing TENG,Xi ZHONG,HaoDi WU,Yan HU,ChangYong ZHOU,XueFeng WANG. Biologic and Transcriptomic Analysis of Citrus hystrix Responses to ‘Candidatus Liberibacter asiaticus’ at Different Infection Stages [J]. Scientia Agricultura Sinica, 2020, 53(7): 1368-1380.