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林麝肺炎克雷伯氏菌的分离鉴定及其kp05372基因的生物信息学分析
赵 位1, 王吴优1, 程建国,等2
1.四川农业大学 动物医学院;2.四川养麝研究所
摘要:
【目的】对1株疑似肺炎克雷伯氏菌进行分离鉴定及全基因测序分析,并对发现的新基因kp05372编码产物进行生物信息学分析。【方法】采用传统的细菌鉴定方法和分子生物学方法,分别对采自麝粪便的1株病原菌的生理生化特征及16S rRNA序列进行测定;以小鼠感染试验和半数致死量 (LD50)测试该病原菌的致病性;用全基因组测序方法对病原菌基因组进行测序分析,并对发现的新基因编码产物进行生物信息学分析。【结果】经生理生化试验和16S rRNA序列分析发现,分离菌株为肺炎克雷伯氏菌,命名为GPKP,其对小鼠致死的LD50为6.3×107 CFU/mL。该菌基因组大小为4 879 707 bp,包含5 490个开放阅读框,共注释到22组COG功能。kp05372基因编码产物由302个氨基酸组成,无信号肽,是一种不稳定的、在细胞内发挥生理作用的亲水性蛋白。【结论】分离的细菌为肺炎克雷伯氏菌,kp05372基因编码产物属于典型的LysR家族转录因子(LTTR)。
关键词:  林麝  肺炎克雷伯氏菌  kp05372  生物信息学分析
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基金项目:四川省学术和技术带头人培养资助项目;四川农业大学双支项目
Isolation and identification of Klebsiella pneumoniae from forest musk deer and bioinformatics analysis of its kp05372 gene
ZHAO Wei,WANG Wuyou,CHENG Jianguo,et al
Abstract:
【Objective】The purpose of this study was to isolate,identify and conduct whole genome sequence analysis ona suspected Klebsiella pneumoniae strain.Bioinformatics analysis was also conducted on the encoding product of a novel gene kp05372.【Method】One pathogen was isolated and identified using the traditional identification and 16S rRNA sequence analysis.The pathogenicity of the pathogen was verified by infection experiment and median lethal dose (LD50) measurement in mice.The genome of pathogen was sequenced using Illumina Miseq technology platform and the structure of novel gene product was predicted by bioinformatics analysis. 【Result】 The isolate was identified as K.pneumoniae and named as GPKP.Pathogenicity test indicated that LD50 in mice was 6.3×107 CFU/mL.The whole genome sequencing showed that the genome of GPKP was 4 879 707 bp with 5 490 open reading frames,and annotation analysis revealed 22 COG functions.The encoding product of kp05372 gene consisted of 302 amino acids without signal peptide.It was a hydrophilic and unstable protein,playing a physiological role in cells.【Conclusion】The pathogen was identified as K.pneumoniae and the kp05372 gene product belonged to LysR type transcriptional regulator (LTTR).
Key words:  forest musk deer  Klebsiella pneumoniae  kp05372  bioinformatics analysis