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密码子使用与抗生素耐药性:一种隐藏的进化机制。

Codon usage and antibiotic resistance: A hidden evolutionary mechanism.

作者信息

Dahal Ujwal, Bansal Anu

机构信息

Department of Biochemistry, School of Bioengineering and Biosciences, Lovely Professional University, 144411, India.

Department of Biochemistry, School of Bioengineering and Biosciences, Lovely Professional University, 144411, India.

出版信息

Biochimie. 2025 Jul 31. doi: 10.1016/j.biochi.2025.07.027.

Abstract

Antibiotic resistance represents a global health crisis, and emerging evidence suggests that codon usage, traditionally considered a silent aspect of genetic coding, plays a pivotal role in the evolution of resistance. Traditional resistance mechanisms, such as efflux pumps, enzymatic inactivation, and target modification, have been extensively studied. Still, recent findings highlight the role of codon optimization in enhancing the synthesis of resistance determinants in pathogens, including Acinetobacter baumannii, Neisseria gonorrhoeae, and Klebsiella pneumoniae. Comparative genomic analyses employing metrics such as Codon Adaptation Index (CAI), Effective Number of Codons (ENC), and Relative Synonymous Codon Usage (RSCU), alongside advanced bioinformatic and machine learning approaches, have identified subtle yet significant shifts in codon usage patterns between resistant and susceptible strains. Additionally, experimental studies using in vitro assays, in vivo models, and synthetic biology approaches prove that translational control through codon modulation contributes to adaptive responses under antibiotic pressure. Understanding these associations offers potential avenues for developing novel diagnostic biomarkers and therapeutic strategies. Therefore, this review underscores the necessity of an interdisciplinary approach to decipher the complex interplay between codon usage and antibiotic resistance, ultimately informing future efforts to mitigate the impact of multidrug-resistant pathogens.

摘要

抗生素耐药性是一场全球健康危机,新出现的证据表明,密码子使用(传统上被认为是遗传编码的一个沉默方面)在耐药性进化中起着关键作用。传统的耐药机制,如外排泵、酶失活和靶点修饰,已经得到了广泛研究。然而,最近的研究结果突出了密码子优化在增强包括鲍曼不动杆菌、淋病奈瑟菌和肺炎克雷伯菌在内的病原体中耐药决定因素合成方面的作用。采用密码子适应指数(CAI)、有效密码子数(ENC)和相对同义密码子使用(RSCU)等指标的比较基因组分析,以及先进的生物信息学和机器学习方法,已经确定了耐药菌株和敏感菌株之间密码子使用模式的细微但显著的变化。此外,使用体外试验、体内模型和合成生物学方法的实验研究证明,通过密码子调控进行的翻译控制有助于在抗生素压力下的适应性反应。理解这些关联为开发新型诊断生物标志物和治疗策略提供了潜在途径。因此,本综述强调了采用跨学科方法来解读密码子使用与抗生素耐药性之间复杂相互作用的必要性,最终为未来减轻多重耐药病原体影响的努力提供信息。

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