Center for Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany.
InfectoGnostics Research Campus, Jena, Germany.
Sci Rep. 2017 Feb 24;7:43232. doi: 10.1038/srep43232.
The secretion of antimicrobial compounds is an ancient mechanism with clear survival benefits for microbes competing with other microorganisms. Consequently, mechanisms that confer resistance are also ancient and may represent an underestimated reservoir in environmental bacteria. In this context, β-lactamases (BLs) are of great interest due to their long-term presence and diversification in the hospital environment, leading to the emergence of Gram-negative pathogens that are resistant to cephalosporins (extended spectrum BLs = ESBLs) and carbapenems (carbapenemases). In the current study, protein sequence databases were used to analyze BLs, and the results revealed a substantial number of unknown and functionally uncharacterized BLs in a multitude of environmental and pathogenic species. Together, these BLs represent an uncharacterized reservoir of potentially transferable resistance genes. Considering all available data, in silico approaches appear to more adequately reflect a given resistome than analyses of limited datasets. This approach leads to a more precise definition of BL clades and conserved motifs. Moreover, it may support the prediction of new resistance determinants and improve the tailored development of robust molecular diagnostics.
抗菌化合物的分泌是一种古老的机制,对与其他微生物竞争的微生物具有明显的生存优势。因此,赋予抗性的机制也是古老的,可能代表了环境细菌中被低估的储备库。在这方面,β-内酰胺酶(BLs)因其在医院环境中的长期存在和多样化而引起了极大的关注,导致对头孢菌素(广谱 BLs=ESBLs)和碳青霉烯类(碳青霉烯酶)具有耐药性的革兰氏阴性病原体的出现。在本研究中,使用蛋白质序列数据库分析了 BLs,结果表明在多种环境和病原体物种中存在大量未知和功能尚未确定的 BLs。这些 BLs 共同代表了一个未被描述的潜在可转移抗性基因储备库。考虑到所有可用的数据,与有限数据集的分析相比,基于计算机的方法似乎更能准确反映给定的耐药组。这种方法可以更精确地定义 BL 进化枝和保守基序。此外,它可能支持对新的耐药决定因素的预测,并有助于开发更稳健的分子诊断方法。