Three drug-resistant strains isolated and identified by Gram stain, urease, oxidase, catalase activity testing, and urease gene PCR testing: the drug resistance information of these strains is summarized in Table 1.
Bacterial sequence information
Based on the valid data from the previous sequencing platform, the CleanData could be assembled for each sample and the optimal assembly results were obtained after multiple adjustments. The assembly sequence was analyzed by correcting single base, circular judgment and plasmid comparison. The results of the genome assembly statistics of each sample are shown in Table 2. These three strains have been uploaded to the NCBI Biosample database: Hpbs1(https://www.ncbi.nlm.nih.gov/biosample/?term=SAMN10461767)
Hpbs2(https://www.ncbi.nlm.nih.gov/biosample/?term=SAMN10663081), and Hpbs3(https://www.ncbi.nlm.nih.gov/biosample/?term=SAMN10663175),
Gene prediction was applied to determine gene composition. The statistics are shown in Table 3 below.
Circular genome analysis
GC skew analysis was performed using (G-C) / (G+C) calculations based on Genomic sequences of sequenced strains. The results of gene distribution, ncRNA distribution and gene annotation are demonstrated in Fig. 1. Hpbs1 had 835 genes, 26 tRNAs, 6 rRNAs, 2 sRNAs in a positive chain. It also had 736 genes, 10 tRNAs, 0 rRNA, 5 sRNAs in negative chain and 157 repeats without positive or negative chain. There are 943 genes, 26 tRNAs, 6 rRNAs, 3 sRNAs, 849 genes, 10 tRNAs, 0 rRNA, 3 sRNAs, and 153 repeats in Hpbs2; 869 genes, 26 tRNAs, 6 rRNAs, 3 sRNAs, 863 genes,10 tRNAs, 0 rRNA, 3 sRNAs, 155 repeats in Hpbs3.
Functional annotation was accomplished by analysis of protein sequences. We aligned genes with databases to obtain their corresponding annotations. To demonstrate the biological meaning, the highest quality alignment result was chosen as a gene annotation. Functional annotation was completed by blasting genes with different databases. In this project we have finished P450, VFDB, ARDB, CAZY, SWISSPROT, NOG, COG, CARD, NR, DBCAN, T3SS, TREMBL, IPR, PHI, KEGG, GO, KOG...17 databases annotations. The annotation results are shown in Tables 4 and 5.
Analysis of drug resistance gene database
The drug resistance gene numbers of three strains were different in the CARD drug resistance database, which are 14, 13 and 15 genes, respectively. However, after sorting, it was found that some genes were repetitive. The specific numbers and characteristics of genes are shown in the Tables 6 and 7. NP_207975.1 and NP_207972.1 were efflux pump genes of 26695 strain, i.e. hp1181 and hp1184 genes. Their drug resistance was verified by RT-PCR as illustrated in Fig. 2. After knocking out the drug resistance gene, drug sensitivity was significantly improved as shown in Fig. 3.
Identification of 23S rRNA gene mutations
Three strains were resistant to clarithromycin, so we analyzed and identified the sites of clarithromycin-resistant mutations. We found that three strains had mutations in A2142G, A2143G, G2144T, and some had mutations in other sites, as shown in Table 8.
Gene mutation induced in drug-resistant strains
After induction with clarithromycin, Hp26695 drug resistance was enhanced on the 12th day, reached the highest level on day 16 and increased to 8μg/ml on the 24th day. The expressions of hp1181 and hp1184 were also increased with increasing clarithromycin resistance, especially hp1184, as shown in Fig. 4. Only A2142G and A 2143G mutations were detected in 23S RNA, with no other mutation sites being found，as shown in Table 9. These data indicated that these two genes may be involved early in the regulation of clarithromycin resistance.