魔芋软腐病病原菌果胶杆菌ZX67菌株全基因组测序及分析

doi:10.11924/j.issn.1000-6850.casb2022-0224

摘要/Abstract

摘要：

菌株ZX67是魔芋软腐病病原菌胡萝卜果胶杆菌胡萝卜亚种(Pectobacterium carotovorum subsp. carotovorum),为进一步了解该病原菌的特性,便于更好地研究防治软腐病的方法,对该菌株进行了全基因组测序和分析。该菌株基因组总长度为4,909,724 bp,GC含量为51.27%,包含4,977个编码基因,其序列长度占总基因组的85.25%,预测的非编码RNA主要包括74个tRNA、22个rRNA及100个sRNA,有10个基因岛,6个转座子,预测存在2个前噬菌体,每个前噬菌体的平均长度为26,258 bp,有5个CRISPR序列,每个序列的平均长度为621 bp,并分析了与降解寄主细胞壁相关的裂解酶、与侵染植物相关的5种蛋白分泌系统。以上结果,为进一步了解软腐病病原菌的特性提供了机会,也为研究新的防治方法提供了新的出发点和思路。

关键词: 胡萝卜果胶杆菌, 软腐病, 魔芋, 全基因组, 测序

Abstract:

Strain ZX67 belonging to Pectobacterium carotovorum subsp. carotovorum is the pathogen of konjac soft rot disease. In order to further understand the characteristics of the pathogen and effectively control and prevent konjac soft rot disease, the whole genome of the strain was sequenced and analyzed. The results showed that its total genome length was 4,909,724 bp and GC-content was 51.27%. It contained 4,977 coding genes, and the sequence accounted for 85.25% of the total genome. The predicted non-coding RNA (ncRNA) mainly included tRNA (74), rRNA (22) and sRNA (100). There were 10 gene islands, and 6 transposons. Two prophages were predicted, the average length of each prophage was 26,258 bp. Five CRISPR sequences were predicted, with the average length of each sequence of 621 bp. In the coding genes, the pectate lyases and other enzymes related to degradation of host plant cells were analyzed. There were five protein secretory systems related to the infected plants. The results provided a new and comprehensive idea for further understanding the characteristics of the pathogen, and studying its prevention and control measures.

Key words: Pectobacterium carotovorum, soft rot disease, Amorphophallus konjac, whole genome, sequence

中图分类号:

Q933

夏涛, 李梦飞, 张雯, 陈雪英, 史银连, 王红莹, 李刚, 祝伟. 魔芋软腐病病原菌果胶杆菌ZX67菌株全基因组测序及分析[J]. 中国农学通报, 2022, 38(29): 52-60.

XIA Tao, LI Mengfei, ZHANG Wen, CHEN Xueying, SHI Yinlian, WANG Hongying, LI Gang, ZHU Wei. Complete Genome Sequence of Pectobacterium carotovorum Strain ZX67: An Plant Pathogen of Amorphophallus konjac Soft Rot Disease[J]. Chinese Agricultural Science Bulletin, 2022, 38(29): 52-60.

图/表 9

参考文献 31

[1]	TESTER R F, AL-GHAZZEWI F H. Beneficial health characteristics of native and hydrolysed konjac (Amorphophallus konjac) glucomannan[J]. J sci food agric., 2016(96):3283-3291.
[2]	WU J, LIU X, DIAO Y, et al. Authentication and characterization of a candidate antagonistic bacterium against soft rot of Amorphophallus konjac[J]. Crop protection, 2012(34):83-87.
[3]	HAUBEN L, MOORE E R, VAUTERIN L, et al. Phylogenetic position of phytopathogens within the Enterobacteriaceae[J]. Syst appl microbiol, 1998, 21(3):384-397. doi: 10.1016/S0723-2020(98)80048-9 URL
[4]	WALERON M, MISZTAK A, WALERON M, et al. Transfer of Pectobacterium carotovorum subsp. carotovorum strains isolated from potatoes grown at high altitudes to Pectobacterium peruviense sp. nov[J]. Syst appl microbiol, 2018, 41(2):85-93. doi: 10.1016/j.syapm.2017.11.005 URL
[5]	MANSFIELD J, GENIN S, MAGORI S, et al. Top 10 plant pathogenic bacteria in molecular plant pathology[J]. Mol Plant Pathol, 2012, 13(6): 614-629. doi: 10.1111/j.1364-3703.2012.00804.x pmid: 22672649
[6]	OSBORNE F M. Short Protocols in Molecular Biology[M]. Science publishing house, 2008:39.
[7]	ROBERTS R J, CARNEIRO M O, SCHATZ M C. The advantages of SMRT sequencing[J]. Genome biology, 2013, 14(7):405. doi: 10.1186/gb-2013-14-6-405 pmid: 23822731
[8]	KANEHISA M, GOTO S, KAWASHIMA S, et al. The KEGG resource for deciphering the genome[J]. Nucleic acids res, 2004, 32(Database issue):277-280. pmid: 14681412
[9]	TATUSOV R L, FEDOROVA N D, JACKSON J D, et al. The COG database: an updated version includes eukaryotes[J]. BMC Bioinformatics, 2003, 4(1):41. doi: 10.1186/1471-2105-4-41 URL
[10]	ASHBURNER M, BALL C A, BLAKE J A, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium[J]. Nat genet, 2000, 25(1):25-29. doi: 10.1038/75556 pmid: 10802651
[11]	LI W, JAROSZEWSKI L, GODZIK A. Tolerating some redundancy significantly speeds up clustering of large protein databases[J]. Bioinformatics, 2002, 18(1):77-82. pmid: 11836214
[12]	AMOS B, ROLF A. The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000[J]. Nucleic acids res, 2000, 28(1):45-48. pmid: 10592178
[13]	MAGRANE M. UniProt Knowledgebase: a hub of integrated protein data[J]. Database:the journal of biological databases and curation, 2011(0):bar009.
[14]	MISTRY J, FINN R. Pfam: a domain-centric method for analyzing proteins and proteomes[J]. Methods mol biol, 2007, 396:43-58. pmid: 18025685
[15]	LOWE T M, EDDY S R. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence[J]. Nucleic acids research, 1997, 25(5):955-964. pmid: 9023104
[16]	LAGESEN K, HALLIN P, RøDLAND EA, et al. RNAmmer: consistent and rapid annotation of ribosomal RNA genes[J]. Nucleic acids res, 2007, 35(9):3100-3108. pmid: 17452365
[17]	GARDNER P P, DAUB J, TATE J G, et al. Rfam: updates to the RNA families database[J]. Nucleic acids research, 2009, 37 (Database issue):136-140. doi: 10.1093/nar/gkn766 pmid: 18953034
[18]	CUI X, LU Z, WANG S, et al. CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction[J]. Bioinformatics (Oxford, England), 2016, 32(12):i332-i340. doi: 10.1093/bioinformatics/btw271 URL
[19]	HSIAO W, WAN I, JONES SJ, et al. IslandPath: aiding detection of genomic islands in prokaryotes[J]. Bioinformatics (Oxford, England), 2003, 19(3):418-420. doi: 10.1093/bioinformatics/btg004 URL
[20]	ZHOU Y, LIANG Y, LYNCH KH, et al. PHAST: a fast phage search tool[J]. Nucleic acids res, 2011, 39(Web Server issue):347-352. doi: 10.1093/nar/gkr485 pmid: 21672955
[21]	SAHA S, BRIDGES S, MAGBANUA ZV, et al. Empirical comparison of ab initio repeat finding programs[J]. Nucleic acids res, 2008, 36(7):2284-2294. doi: 10.1093/nar/gkn064 pmid: 18287116
[22]	BENSON G. Tandem repeats finder: a program to analyze DNA sequences[J]. Nucleic acids res, 1999, 27(2):573-580. pmid: 9862982
[23]	GRISSA I1 VERGNAUD G, POURCEL C. CRISPRFinder: a web tool to identify clustered regularly interspaced short palindromic repeats[J]. Nucleic acids res, 2007, 35(Web Server issue):52-57. pmid: 17537822
[24]	KRZYWINSKI M, SCHEIN J, BIROL I, et al. Circos: an information aesthetic for comparative genomics[J]. Genome res, 2009, 19(9):1639-1645. doi: 10.1101/gr.092759.109 pmid: 19541911
[25]	NIEMI O, LAINE P, KOSKINEN P, et al. Genome sequence of the model plant pathogen Pectobacterium carotovorum SCC1[J]. Stand genomic sci, 2017, 12(1):1-8. doi: 10.1186/s40793-016-0218-y URL
[26]	HYATT D, CHEN GL, LOCASCIO PF, et al. Prodigal: prokaryotic gene recognition and translation initiation site identification[J]. BMC bioinformatics, 2010, 11(1):119. doi: 10.1186/1471-2105-11-119 URL
[27]	TATUSOVA T, DICUCCIO M, BADRETDIN A, et al. NCBI prokaryotic genome annotation pipeline[J]. Nucleic acids res, 2016, 44(14):6614-6624. doi: 10.1093/nar/gkw569 pmid: 27342282
[28]	JACOBSEN T, BARDIAUX B, FRANCETIC O, et al. Structure and function of minor pilins of type IV pili[J]. Medical microbiology and immunology, 2020, 209(3):301-308. doi: 10.1007/s00430-019-00642-5 pmid: 31784891
[29]	CHARKOWSKI A, BLANCO C, CONDEMINE G, et al. The role of secretion systems and small molecules in soft-rot enterobacteriaceae pathogenicity[J]. Annu rev phytopathol, 2012, 50(1):425-449. doi: 10.1146/annurev-phyto-081211-173013 URL
[30]	NAVARRO-GARCIA F, RUIZ-PEREZ F, CATALDI Á, et al. Type VI Secretion System in Pathogenic Escherichia coli: Structure, Role in Virulence, and Acquisition[J]. Front microbiol, 2019, 10:1965. doi: 10.3389/fmicb.2019.01965 URL
[31]	MCCARTHY R R, YU M, EILERS K, et al. Cyclic di-GMP inactivates T6SS and T4SS activity in Agrobacterium tumefaciens[J]. Mol microbiol, 2019, 112(2):632-648. doi: 10.1111/mmi.14279 URL

Items	Stat
Total Contig number	1
Max Contig length	4,909,724
Min Contig length	4,909,724
Squence GC	51.27%
Contig N50 length	4,909,724

Items	Stat
Total Contig number	1
Max Contig length	4,909,724
Min Contig length	4,909,724
Squence GC	51.27%
Contig N50 length	4,909,724

Genome features	Stat	In Genome/%
Genome size	4,909,724 bp	100.00
Squence GC	2,517,215 bp	51.27
coding genes	4,977×1,041 bp	85.25
interspersed nuclear elements(bp)	261×88 bp	0.47
Tandem Repeat(bp)	103×235 bp	0.49
ncRNA	45,076 bp	0.92
Genomics Islands	10×36,027 bp	7.3
Transposon	6×363 bp	0.04
Prophage	2×26,258 bp	1.07
CRISPR	5×621 bp	0.06

Genome features	Stat	In Genome/%
Genome size	4,909,724 bp	100.00
Squence GC	2,517,215 bp	51.27
coding genes	4,977×1,041 bp	85.25
interspersed nuclear elements(bp)	261×88 bp	0.47
Tandem Repeat(bp)	103×235 bp	0.49
ncRNA	45,076 bp	0.92
Genomics Islands	10×36,027 bp	7.3
Transposon	6×363 bp	0.04
Prophage	2×26,258 bp	1.07
CRISPR	5×621 bp	0.06

CRISPR_id	Start	End	CRISPR Length	DR_consensus	DR_length	Number of spacers
Crispr_1	859546	860418	872	TTTCTAAGCTGCCTATGCGGCAGTGAAC	28	14
Crispr_2	868987	870516	1529	GTTCACTGCCGGATAGGCAGCTTAGAAA	28	25
Crispr_3	878333	878841	508	TTTTCTAAGCTGCCTATCCGGCAGTGAAC	29	8
Possible Crispr_4	2896052	2896150	98	CGGGCCGTTGCTACGCAACGTTGAA	25	1
Possible Crispr_5	3472205	3472305	100	GACGGACAAGGATGTCCGCCATAAAAAAA	29	1