{"title":"Prediction of protein structural changes mediated by NS-SNPs in antibiotic resistance determinants in Streptococcus pneumoniae","authors":"Wenjia Liu, Xin Rao","doi":"10.1007/s00203-025-04444-7","DOIUrl":null,"url":null,"abstract":"<div><p><i>Streptococcus pneumoniae</i> (<i>S. pneumoniae</i>) is a gram-positive bacterium, which is a human pathogen that colonises the human nasopharyngeal region. The evolution of its resistance to many antibiotics has become a major clinical and public health problem. In a study of <i>S. pneumoniae</i>, it was found that resistant strains contained more non-synonymous single nucleotide polymorphisms (NS-SNPs) than sensitive strains. These findings motivate us to further understand the role of NS-SNP mutation in bacterial drug-resistance and how it mediates the development of <i>S. pneumoniae</i> drug-resistance. NS-SNP is a molecular genetic marker that has been widely used in the field of disease and microbial drug-resistance. However, few studies have analyzed the characteristics and related mechanisms of microbial drug-resistance through the effect of NS-SNP mutation on protein conformation and function. Therefore, based on NS-SNP mutation, this study predicted the homologous resistance proteins related to <i>S. pneumoniae</i> and explored the resistance mechanism of homologous proteins mediated by NS-SNP mutation. SNP identification was first implemented by using MUMmer 3 software for whole-genome sequence alignment. The self-designed Fast Feature Selection (FFS) and Codon Mutation Detection (CMD) machine learning algorithms were used for feature extraction and NS-SNPs detection, respectively, ten NS-SNPs mutations were finally selected. The protein/homologous protein structure was predicted and evaluated by ab initio method and Swiss-Model server. Subsequently, Molecular Operating Environment (MOE) software was used to compare protein structure and superposition. Finally, the impact of NS-SNPs on the electrostatic surface of proteins was also evaluated by PyMOL software. This study found that three NS-SNPs mutation-mediated homologous proteins were closely related to drug-resistance of <i>S. pneumoniae</i>, namely NS-SNPs (ID 247805, 817989) mutations-mediated antibiotic resistant ABCF (ARE-ABCF) transporter, and NS-SNP (ID 1101585) mutation-mediated NorM protein promoting antibiotic resistance of <i>S. pneumoniae</i>. Moreover, the resistance might be caused by the difference in electrostatic potential energy resulting from the NS-SNP mutations. This suggests that changes in the electrostatic environment might affect antibiotic binding affinity, revealing a novel mechanism of bacterial drug resistance. Furthermore, this study also provides information on the antibiotic resistance of <i>S. pneumoniae</i>, laying the foundation for its clinical research, diagnosis and medication to treat bacterial infections.</p></div>","PeriodicalId":8279,"journal":{"name":"Archives of Microbiology","volume":"207 10","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Microbiology","FirstCategoryId":"99","ListUrlMain":"https://link.springer.com/article/10.1007/s00203-025-04444-7","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Streptococcus pneumoniae (S. pneumoniae) is a gram-positive bacterium, which is a human pathogen that colonises the human nasopharyngeal region. The evolution of its resistance to many antibiotics has become a major clinical and public health problem. In a study of S. pneumoniae, it was found that resistant strains contained more non-synonymous single nucleotide polymorphisms (NS-SNPs) than sensitive strains. These findings motivate us to further understand the role of NS-SNP mutation in bacterial drug-resistance and how it mediates the development of S. pneumoniae drug-resistance. NS-SNP is a molecular genetic marker that has been widely used in the field of disease and microbial drug-resistance. However, few studies have analyzed the characteristics and related mechanisms of microbial drug-resistance through the effect of NS-SNP mutation on protein conformation and function. Therefore, based on NS-SNP mutation, this study predicted the homologous resistance proteins related to S. pneumoniae and explored the resistance mechanism of homologous proteins mediated by NS-SNP mutation. SNP identification was first implemented by using MUMmer 3 software for whole-genome sequence alignment. The self-designed Fast Feature Selection (FFS) and Codon Mutation Detection (CMD) machine learning algorithms were used for feature extraction and NS-SNPs detection, respectively, ten NS-SNPs mutations were finally selected. The protein/homologous protein structure was predicted and evaluated by ab initio method and Swiss-Model server. Subsequently, Molecular Operating Environment (MOE) software was used to compare protein structure and superposition. Finally, the impact of NS-SNPs on the electrostatic surface of proteins was also evaluated by PyMOL software. This study found that three NS-SNPs mutation-mediated homologous proteins were closely related to drug-resistance of S. pneumoniae, namely NS-SNPs (ID 247805, 817989) mutations-mediated antibiotic resistant ABCF (ARE-ABCF) transporter, and NS-SNP (ID 1101585) mutation-mediated NorM protein promoting antibiotic resistance of S. pneumoniae. Moreover, the resistance might be caused by the difference in electrostatic potential energy resulting from the NS-SNP mutations. This suggests that changes in the electrostatic environment might affect antibiotic binding affinity, revealing a novel mechanism of bacterial drug resistance. Furthermore, this study also provides information on the antibiotic resistance of S. pneumoniae, laying the foundation for its clinical research, diagnosis and medication to treat bacterial infections.
期刊介绍:
Research papers must make a significant and original contribution to
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