Departamento de Biotecnología Microbiana, Centro Nacional de Biotecnología, CSIC , Darwin 3, Cantoblanco, 28049, Madrid , Spain.
Ups J Med Sci. 2014 May;119(2):68-77. doi: 10.3109/03009734.2014.901444. Epub 2014 Mar 30.
The emergence and spread of antibiotic resistance among human pathogens is a relevant problem for human health and one of the few evolution processes amenable to experimental studies. In the present review, we discuss some basic aspects of antibiotic resistance, including mechanisms of resistance, origin of resistance genes, and bottlenecks that modulate the acquisition and spread of antibiotic resistance among human pathogens. In addition, we analyse several parameters that modulate the evolution landscape of antibiotic resistance. Learning why some resistance mechanisms emerge but do not evolve after a first burst, whereas others can spread over the entire world very rapidly, mimicking a chain reaction, is important for predicting the evolution, and relevance for human health, of a given mechanism of resistance. Because of this, we propose that the emergence and spread of antibiotic resistance can only be understood in a multi-parameter space. Measuring the effect on antibiotic resistance of parameters such as contact rates, transfer rates, integration rates, replication rates, diversification rates, and selection rates, for different genes and organisms, growing under different conditions in distinct ecosystems, will allow for a better prediction of antibiotic resistance and possibilities of focused interventions.
抗生素耐药性在人类病原体中的出现和传播是一个与人类健康相关的问题,也是少数几个可进行实验研究的进化过程之一。在本综述中,我们讨论了抗生素耐药性的一些基本方面,包括耐药机制、耐药基因的起源以及调节人类病原体获得和传播抗生素耐药性的瓶颈。此外,我们分析了调节抗生素耐药性进化景观的几个参数。了解为什么有些耐药机制出现后不会在第一次爆发后进化,而另一些机制可以在全球范围内迅速传播,就像连锁反应一样,对于预测给定耐药机制的进化及其对人类健康的相关性非常重要。因此,我们提出,只有在多参数空间中才能理解抗生素耐药性的出现和传播。测量不同基因和生物体在不同生态系统中不同条件下的接触率、转移率、整合率、复制率、多样化率和选择率等参数对抗生素耐药性的影响,将有助于更好地预测抗生素耐药性,并有可能进行有针对性的干预。