Hegreness Matthew, Shoresh Noam, Damian Doris, Hartl Daniel, Kishony Roy
Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, MA 02115, USA.
Proc Natl Acad Sci U S A. 2008 Sep 16;105(37):13977-81. doi: 10.1073/pnas.0805965105. Epub 2008 Sep 8.
The emergence of resistance during multidrug chemotherapy impedes the treatment of many human diseases, including malaria, TB, HIV, and cancer. Although certain combination therapies have long been known to be more effective in curing patients than single drugs, the impact of such treatments on the evolution of drug resistance is unclear. In particular, very little is known about how the evolution of resistance is affected by the nature of the interactions--synergy or antagonism--between drugs. Here we directly measure the effect of various inhibitory and subinhibitory drug combinations on the rate of adaptation. We develop an automated assay for monitoring the parallel evolution of hundreds of Escherichia coli populations in a two-dimensional grid of drug gradients over many generations. We find a correlation between synergy and the rate of adaptation, whereby evolution in more synergistic drug combinations, typically preferred in clinical settings, is faster than evolution in antagonistic combinations. We also find that resistance to some synergistic combinations evolves faster than resistance to individual drugs. The accelerated evolution may be due to a larger selective advantage for resistance mutations in synergistic treatments. We describe a simple geometric model in which mutations conferring resistance to one drug of a synergistic pair prevent not only the inhibitory effect of that drug but also its enhancing effect on the other drug. Future study of the profound impact that synergy and other drug-pair properties can have on the rate of adaptation may suggest new treatment strategies for combating the spread of antibiotic resistance.
多药化疗过程中耐药性的出现阻碍了包括疟疾、结核病、艾滋病和癌症在内的许多人类疾病的治疗。虽然长期以来人们都知道某些联合疗法在治愈患者方面比单一药物更有效,但这种治疗方法对耐药性演变的影响尚不清楚。特别是,对于耐药性的演变如何受到药物之间相互作用的性质(协同或拮抗)的影响,人们了解得非常少。在这里,我们直接测量了各种抑制性和亚抑制性药物组合对适应率的影响。我们开发了一种自动化检测方法,用于监测数百个大肠杆菌群体在二维药物梯度网格中多代的平行进化。我们发现协同作用与适应率之间存在相关性,即在临床环境中通常更受青睐的协同性更强的药物组合中的进化速度比拮抗性组合中的进化速度更快。我们还发现,对某些协同组合的耐药性进化速度比对单一药物的耐药性进化速度更快。进化加速可能是由于协同治疗中耐药突变具有更大的选择优势。我们描述了一个简单的几何模型,其中赋予对协同药物对中一种药物耐药性的突变不仅会阻止该药物的抑制作用,还会阻止其对另一种药物的增强作用。对协同作用和其他药物对特性可能对适应率产生的深远影响的未来研究,可能会为对抗抗生素耐药性的传播提出新的治疗策略。