Application of next-generation sequencing to characterize novel mutations in clarithromycin-susceptible Helicobacter pylori strains with A2143G of 23S rRNA gene.

BACKGROUND: Clarithromycin (CLR) resistance has become a predominant factor for treatment failure of Helicobacter pylori eradication. Although the molecular mechanism of CLR resistance has been clearly understood in H. pylori, it is lack of evidence of other genes involved in drug resistance. Furthermore, the molecular mechanism of phenotype susceptible to CLR while genotype of 23S rRNA is mutant with A2143G is unclear. Here, we characterized the mutations of CLR-resistant and -susceptible H. pylori strains to explore bacterial resistance. METHODS: In the present study, the whole genomes of twelve clinical isolated H. pylori strains were sequenced, including two CLR-susceptible strains with mutation of A2143G. Single nucleotide variants (SNVs) were extracted and analyzed from multidrug efflux transporter genes. RESULTS: We did not find mutations associated with known CLR-resistant sites except for controversial T2182C outside of A2143G in the 23S rRNA gene. Although total SNVs of multidrug efflux transporter gene and the SNVs of HP0605 were significant differences (P ≤ 0.05) between phenotype resistant and susceptible strains. There is no significant difference in SNVs of RND or MFS (HP1181) family. However, the number of mutations in the RND family was significantly higher in the mutant strain (A2143G) than in the wild type. In addition, three special variations from two membrane proteins of mtrC and hefD were identified in both CLR-susceptible strains with A2143G. CONCLUSIONS: Next-generation sequencing is a practical strategy for analyzing genomic variation associated with antibiotic resistance in H. pylori. The variations of membrane proteins of the RND family may be able to participate in the regulation of clinical isolated H. pylori susceptibility profiles.

Self-powered Real-time Movement Monitoring Sensor Using Triboelectric Nanogenerator Technology.

The triboelectric nanogenerator (TENG) has great potential in the field of self-powered sensor fabrication. Recently, smart electronic devices and movement monitoring sensors have attracted the attention of scientists because of their application in the field of artificial intelligence. In this article, a TENG finger movement monitoring, self-powered sensor has been designed and analysed. Under finger movements, the TENG realizes the contact and separation to convert the mechanical energy into electrical signal. A pulse output current of 7.8 µA is generated by the bending and straightening motions of the artificial finger. The optimal output power can be realized when the external resistance is approximately 30 MΩ. The random motions of the finger are detected by the system with multiple TENG sensors in series. This type of flexible and self-powered sensor has potential applications in artificial intelligence and robot manufacturing.