铜绿假单胞菌对鲎素耐药前后的差异表达基因及SNP变化研究

doi:10.13560/j.cnki.biotech.bull.1985.2020-1445

摘要/Abstract

摘要：

为了探讨铜绿假单胞菌对鲎素抗菌肽的耐药性机制,在转录组水平上通过对铜绿假单胞菌抗鲎素突变株和原始菌株的差异表达基因以及差异表达的sRNA靶基因、SNP的变化进行分析。结果表明,通过GO功能和KEGG通路富集发现差异表达基因与细胞膜的组成部分、核苷酸结合、甲酸脱氢酶（NAD+）活性等功能有关,但无显著富集通路;其中有22个差异表达基因发生SNP的碱基突变,涉及到编码脂质A脱酰基酶、外膜蛋白、冷休克蛋白、以及与脂多糖的修饰相关等已知基因和一些编码的假定蛋白有关。进一步预测与分析找到11个差异表达的sRNA和对应的863个差异表达靶基因,这些sRNA靶基因主要与组氨酸生物合成、高丝氨酸激酶活性、5-羧甲基-2-羟基黏液酸δ-异构酶活性功能最相关。推测铜绿假单胞菌对鲎素的耐药性可能是通过影响氨基酸合成与代谢、膜蛋白的形成与修饰、铁离子代谢等途径来调控的,并使极个别基因发生碱基突变,同时sRNA通过作用于相关的靶基因发挥其调控作用。对于发生SNP突变的基因及sRNA对其靶基因mRNA调控有待进一步验证。

关键词: 铜绿假单胞菌, 转录组测序, sRNA, SNP, 靶基因, 富集分析

Abstract:

To explore the resistance mechanism of Pseudomonas aeruginosa to antibacterial peptide tachyplesin I,we employed RNA sequencing to analyze the changes of differentially expressed genes,sRNA target genes,and SNP between tachyplesin I-resistant strain and the original strain. By GO function and KEGG pathway enrichment,the results showed that differentially expressed genes were the most related to the functions of integral component of membrane,nucleotide binding,formate dehydrogenase（NAD+）activity,and there was no significant enrichment pathway. SNP of 22 differentially expressed genes changed,which was related to known genes encoding lipid A deacylase,outer membrane protein,cold shock protein,and lipopolysaccharide modification and hypothesized proteins. Further prediction and analysis uncovered 11 differentially expressed sRNAs and corresponding 863 differentially expressed target genes. The functions of these sRNA target genes were mainly related to histidine biosynthetic process,homoserine kinase activity,and 5-carboxymethyl-2-hydroxymuconate delta-isomerase activity. It is referred that the resistance mechanism of P. aeruginosa to tachyplesin I may be regulated by affecting the synthesis and metabolism of amino acids,the formation and modification of membrane proteins,and metabolism of iron ions,as well as by leading to the base mutations of few genes. At the same time,sRNA played its regulatory role by acting these related target genes expression. The SNP mutated genes and its mRNA regulations to their target genes by sRNA remain to be further verified.

Key words: Pseudomonas aeruginosa, RNA sequencing, sRNA, SNP, target genes, enrichment analysis

洪军, 卫夏怡, 吉冰洁, 叶延欣, 程天赐. 铜绿假单胞菌对鲎素耐药前后的差异表达基因及SNP变化研究[J]. 生物技术通报, 2021, 37(9): 191-202.

HONG Jun, WEI Xia-yi, JI Bing-jie, YE Yan-xin, CHENG Tian-ci. Change of Differentially Expressed Genes and SNP Before or After Pseudomonas aeruginosa Resistance to Tachyplesin I[J]. Biotechnology Bulletin, 2021, 37(9): 191-202.

图/表 11

图1 PA1.2620 与 PA-99 菌株差异基因的 GO 富集图横坐标为 -log10（P-value）,横坐标越大,表示差异表达基因在该功能注释结果中的富集显著性越可靠。统计学上认为,P-value<0.05 是显著水平,P-value <0.01 是极显著水平。纵坐标为 GO term。下同

Fig. 1 GO enrichment analysis of differentially expressed genes between PA1.2620 vs. PA-99 strains. The abscissa is -log10（P-value）. The bigger the value of the abscissa,the more reliable the enrichment significance of differentially expressed genes in the functional annotation results. P-value<0.05 is the significant difference,and P-value<0.01 is the most significant difference. The ordinate is GO term. The same below

图2 PA1.2620与PA-99菌株差异基因的KEGG富集图图中每一个图形表示一个KEGG通路,通路名称见右侧图例。横坐标为富集因子（Enrichment factor）,表示所有基因中注释到某通路的基因比例与差异基因中注释到该通路的基因比例的比值。富集因子越小,表示差异表达基因在该通路中的富集水平越显著。纵坐标为-log10（Q-value）,其中Q-value为多重假设检验校正之后的P-value。因此,纵坐标越大,表示差异表达基因在该通路中的富集显著性越可靠。一般认为,Q-value<0.05是显著水平,Q-value<0.01是极显著水平。下同

Fig.2 KEGG pathway enrichment analysis of differentially expressed genes between PA1.2620 vs. PA-99 strains Each graph in the figure represents one KEGG pathway,whose name is shown in the legend on the right. The abscissa is the enrichment factor,enrichment factor = amount of all genes/amount of DEGs enriched in the pathway in the background gene set. The smaller the enrichment factor,the more significant the enrichment level of differentially expressed genes in this pathway. The ordinate is -log10（Q-value）,where Q-value is the P-value after the correction of multiple hypothesis testing. Therefore,the larger the ordinate,the more reliable the enrichment significance of differentially expressed genes in this pathway. It is generally believed that Q-value<0.05 is the significance difference,Q-value<0.01 is the most significant difference. The same below

图3 RT-qPCR验证结果

Fig. 3 RT-qPCR validation results

表1 SNP位点统计表

Table 1 Statistical table of SNP sites

PA-99突变株样品 Sample of PA-99 mutant	Number of SNP	Transition	Transversion	Heterozygosity
T09	139	75.54%	23.74%	0.72%
T10	226	86.73%	12.83%	0.44%
T11	126	72.22%	26.98%	0.79%

图4 PA-99突变株样品的SNP突变类型分布图

Fig. 4 Distribution of SNP mutation types in PA-99 mutant samples

表2 PA1.2620与PA-99菌株差异表达基因的SNP信息

Table 2 SNP analysis of differentially expressed genes in PA1.2620 vs. PA-99 strains

#ID or Gene name	Protein name	log₂FC	Regulated	Start	End	SNP number	SNP
pvdL	Peptide synthase	1.15621	Up	2707666	2720694	2	2712019C>A;2715424T>C
Novel_244	—	-1.71631	Down	1720641	1732256	1	1732254T>C
PA1938	Hypothetical protein	-1.95428	Down	2118926	2119747	1	2119153T>C
Novel_497	—	1.95302	Up	3672989	3674050	1	3673743G>A
Novel_745	—	2.58303	Up	5130955	5135726	1	5130955T>C
Novel_797	—	-1.77794	Down	5343486	5344904	1	5344709G>A
Novel_840	—	-2.52117	Down	5621609	5624734	1	5621617G>A
PA1428a	Hypothetical protein	1.07562	Up	1552566	1554155	1	1553722G>A
PA0193	Hypothetical protein	1.186966	Up	221585	222487	1	222358C>T
exoY	Adenylate cyclase	-1.75024	Down	2410344	2411480	1	2411150G>T
PA2451	Hypothetical protein	1.56984	Up	2752866	2754445	1	2754392G>A
cspD	Cold-shock protein CspD	-1.0514	Down	2965201	2965473	1	2965461C>T
PA2712	Hypothetical protein	-1.01673	Down	3066296	3067159	1	3066971A>G
PA3380	Hypothetical protein	2.27038	Up	3787021	3787479	1	3787410G>A
opr86	Outer membrane protein Opr86	-1.51418	Down	4085062	4087455	1	4085961C>G
cupB3	Usher CupB3	-1.59417	Down	4565421	4567955	1	4565913A>G
fepD	Ferric enterobactin transporter FepD	1.26932	Up	4655368	4656390	1	4656097T>C
pagL	Lipid A 3-O-deacylase	-2.39699	Down	5229459	5229980	1	5229837C>T
pmrB	Two-component regulator system Signal sensor kinase PmrB	1.00016	Up	5364760	5366193	1	5364817G>T
PA4837	Hypothetical protein	1.411356	Up	5427716	5429842	1	5428274G>A
bioD	ATP-dependent dethiobiotin Synthetase BioD	1.47708	Up	563549	564235	1	563798C>T
vreR	Sigma factor regulator VreR	1.68468	Up	735487	736446	1	735564C>T

表3 PA1.2620与PA-99菌株差异表达sRNA

Table 3 sRNA of differentially expressed genes in PA1.2620 vs. PA-99 strains

sRNA ID	Gene length/nt	log₂FC	Regulated	sRNA ID	Gene length/nt	log₂FC	Regulated
Novel_33	188	-3.101050802	Down	Novel_346	136	-1.138061426	Down
Novel_377	378	-2.065876992	Down	Novel_593	127	-1.434477351	Down
Novel_583	78	-3.461144761	Down	Novel_683	153	-1.371013476	Down
Novel_584	116	-2.305895532	Down	Novel_344	60	1.764469442	Up
Novel_6	94	-1.576755833	Down	Novel_5	284	-1.660811503	Down
Novel_853	117	-1.507421364	Down

图5 PA1.2620与PA-99菌株差异表达的sRNA靶基因数目统计图

Fig.5 Statistical diagram of the number of sRNA target genes of differentially expressed genes in PA1.2620 vs. PA-99 strains

图6 PA1.2620与PA-99菌株表达差异sRNA靶基因的GO富集图

Fig.6 GO enrichment of sRNA target genes of DEGs in PA1.2620 vs. PA-99 strains

图7 PA1.2620与PA-99菌株表达差异sRNA靶基因的KEGG富集图

Fig.7 KEGG enrichment of differentially expressed sRNA target genes in PA1.2620 vs. PA-99 strains

表4 sRNA相关靶基因的SNP变化分析

Table 4 SNP analysis of sRNA target genes

Gene ID	Protein name	log₂FC	Regulated	Start	End	SNP number	SNP
pvdL	Peptide synthase	1.156212	Up	2707666	2720694	2	2712019C>A;2715424T>C
vreR	Sigma factor regulator VreR	1.684682	Up	735487	736446	1	735564C>T
Novel_497	—	1.953026	Up	3672989	3674050	1	3673743G>A
Novel_745	—	2.583033	Up	5130955	5135726	1	5130955T>C
opr86	Outer membrane protein Opr86	-1.51418	Down	4085062	4087455	1	4085961C>G
cupB3	Usher CupB3	-1.59417	Down	4565421	4567955	1	4565913A>G
pmrB	Two-component regulator System signal sensor kinase	1.000160	Up	5364760	5366193	1	5364817G>T
Novel_840	—	-2.52116	Down	5621609	5624734	1	5621617G>A
PA2451	Hypothetical protein	1.569849	Up	2752866	2754445	1	2754392G>A
PA2712	Hypothetical protein	-1.01672	Down	3066296	3067159	1	3066971A>G

参考文献 22

[1]	Nakamura T, Furunaka H, Miyata T, et al. Tachyplesin, a class of antimicrobial peptide from the hemocytes of the horseshoe crab(Tachypleus tridentatus)isolation and chemical structure[J]. Journal of Biological Chemistry, 1988, 263:16709-16713. pmid: 3141410
[2]	Anaya-López1 JL, López-Meza JE. Bacterial resistance to cationic antimicrobial peptides[J]. Critical Reviews in Microbiology, 2013, 39(2):180-195. doi: 10.3109/1040841X.2012.699025 pmid: 22799636
[3]	Cai Y, Chai D, Wang R, et al. Colistin resistance of Acinetobacter baumannii:clinical reports, mechanisms and antimicrobial strategies[J]. Antimicrobial Agents and Chemotherapy, 2012, 67:1607-1615.
[4]	Hong J, Hu JY, Ke F. Experimental induction of bacterial resistance to the antimicrobial peptide tachyplesin I and investigation of the resistance mechanisms[J]. Antimicrobial Agents and Chemotherapy, 2016, 60(10):6067-6075. doi: 10.1128/AAC.00640-16 pmid: 27480861
[5]	洪军, 胡建业, 刘坤, 等. 绿脓杆菌对鲎素耐受性特点及耐受性机制[J]. 微生物学报, 2018, 58(9):1593-1604.
	Hong J, Hu JY, Liu K, et al. Characteristics and resistance of tachyplesin-I resistance in Pseudomonas aeruginosa[J]. Acta Microbiologica Sinica, 2018, 58(9):1593-1604.
[6]	Peng T, Kan J, Lun JS, et al. Identification of novel sRNAs involved in oxidative stress response in the fish pathogen Vibrio alginolyticus by transcriptome analysis[J]. Journal of Fish Diseases, 2019, 42(2):1-15.
[7]	Barnhill EC, Crucello A, Houserova D, et al. Characterization of novel small RNAs(sRNAs)contributing to the desiccation response of Salmonella enterica serovar Typhimurium[J]. RNA Biology, 2019, 16(11):1643-1657. doi: 10.1080/15476286.2019.1653680 URL
[8]	叶中杨, 邱怀雨, 祝丙华, 等. sRNA调控细菌耐药相关基因表达研究进展[J]. 中国生物工程杂志, 2018, 38(7):89-93.
	Ye ZY, Qiu HY, Zhu BH, et al. Research progress of sRNA regulates the expression of genes in related with bacterial resistance[J]. China Biotechnology, 2018, 38(7):89-93.
[9]	Miller CL, Manuel R, Rajasekhar KSL, et al. RsmW, Pseudomonas aeruginosa small non-coding RsmA-binding RNA upregulated in biofilm versus planktonic growth conditions[J]. BMC Microbiology, 2016, 16(1):155. doi: 10.1186/s12866-016-0771-y URL
[10]	刘翠翠. 福氏志贺菌耐药株的转录组测定及sRNA差异分析[D]. 北京:中国农业科学院, 2014.
	Liu CC. The transcriptome sequencing analysis and sRNA difference analysis in drug-resistant Shigella flexneri[D]. Beijing:Chinese Academy of Agricultural Sciences, 2014.
[11]	Zhang YF, Han K, Chandler CE, et al. Probing the sRNA regulatory landscapeof P. aeruginosa:post-transcriptional control of determinants of pathogenicity and antibiotic susceptibility[J]. Molecular Microbiology, 2017, 106(6):919-937. doi: 10.1111/mmi.2017.106.issue-6 URL
[12]	张栋, 高风英, 卢迈新, 等. 尼罗罗非鱼β2 m基因SNP位点和单倍型与无乳链球菌抗性的关联分析[J]. 水生生物学报, 2018, 42(5):903-912.
	Zhang D, Gao FY, Lu MX, et al. Association analysis of SNP locus and haplotype of β2m gene in Nile tilapia(Oreochromis niloticus)with its resistance to Streptococcus agalactiae[J]. Acta Hydrobiologica Sinica, 2018, 42(5):903-912.
[13]	Wang L, Feng Z, Wang X, et al. DEGseq:an R package for identifying differentially expressed genes from RNAseq data[J]. Bioinformatics, 2010, 26:136-138. doi: 10.1093/bioinformatics/btp612 URL
[14]	Ashburner M, Ball CA, Blake JA, et al. Gene ontology:tool for the unification of biology[J]. Nature Genetics, 2000, 25(1):2529.
[15]	Kanehisa M, Goto S, Kawashima S, et al. The KEGG resource for deciphering the genome[J]. Nucleic Acids Research, 2004, 32:D277280.
[16]	Winsor GL, Griffiths EJ, Lo R, et al. Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database[J]. Nucleic Acids Research, 2016, 44:D646-D653. doi: 10.1093/nar/gkv1227 URL
[17]	Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T))Method[J]. Methods, 2001, 25:402-408. pmid: 11846609
[18]	McPhee JB, Bains M, Winsor G, et al. Contribution of the PhoP-PhoQ and PmrA-PmrB two-component regulatory systems to Mg²⁺-induced gene regulation in Pseudomonas aeruginosa[J]. Journal of Bacteriology, 2006, 188:3995-4006. doi: 10.1128/JB.00053-06 URL
[19]	Moskowitz SM, Brannon MK, Dasgupta N, et al. PmrB mutations promote polymyxin resistance of Pseudomonas aeruginosa isolated from colistin-treated cystic fibrosis patients[J]. Antimicrobial Agents and Chemotherapy, 2012, 56(2):1019-1030. doi: 10.1128/AAC.05829-11 pmid: 22106224
[20]	Shepherd J, Ibba M. Direction of aminoacylated transfer RNAs into antibiotic synjournal and peptidoglycan-mediated antibiotic resistance[J]. FEBS Letters, 2013, 587(18):2895-2904. doi: 10.1016/j.febslet.2013.07.036 URL
[21]	Ernst CM, Peschel A. Broad-spectrum antimicrobial peptide resistance by MprF-mediated aminoacylation and flipping of phospholipids[J]. Molecular Microbiology, 2011, 80:290-299. doi: 10.1111/mmi.2011.80.issue-2 URL
[22]	许达, 宗树成, 胡森, 等. 细菌sRNA代谢调控的研究进展[J]. 中国预防兽医学报, 2017, 39(1):80-84.
	Xu D, Zong SC, Hu S, et al. Research progress on regulation of Bacterial sRNA metabolism[J]. Chinese Journal of Preventive Veterinary Medicine, 2017, 39(1):80-84.