Handel Andreas, Margolis Elisa, Levin Bruce R
Department of Biology, Emory University, Atlanta, GA 30322, USA.
J Theor Biol. 2009 Feb 21;256(4):655-62. doi: 10.1016/j.jtbi.2008.10.025. Epub 2008 Nov 8.
For many bacterial infections, drug resistant mutants are likely present by the time antibiotic treatment starts. Nevertheless, such infections are often successfully cleared. It is commonly assumed that this is due to the combined action of drug and immune response, the latter facilitating clearance of the resistant population. However, most studies of drug resistance emergence during antibiotic treatment focus almost exclusively on the dynamics of bacteria and the drug and neglect the contribution of immune defenses. Here, we develop and analyze several mathematical models that explicitly include an immune response. We consider different types of immune responses and investigate how each impacts the emergence of resistance. We show that an immune response that retains its strength despite a strong drug-induced decline of bacteria numbers considerably reduces the emergence of resistance, narrows the mutant selection window, and mitigates the effects of non-adherence to treatment. Additionally, we show that compared to an immune response that kills bacteria at a constant rate, one that trades reduced killing at high bacterial load for increased killing at low bacterial load is sometimes preferable. We discuss the predictions and hypotheses derived from this study and how they can be tested experimentally.
对于许多细菌感染，在开始抗生素治疗时可能就已经存在耐药突变体。然而，这类感染通常能被成功清除。人们普遍认为这是药物和免疫反应共同作用的结果，后者有助于清除耐药菌群体。然而，大多数关于抗生素治疗期间耐药性产生的研究几乎完全集中在细菌和药物的动态变化上，而忽略了免疫防御的作用。在此，我们开发并分析了几个明确包含免疫反应的数学模型。我们考虑了不同类型的免疫反应，并研究每种反应如何影响耐药性的产生。我们发现，一种尽管在药物诱导下细菌数量大幅下降但仍保持强度的免疫反应，能显著减少耐药性的产生，缩小突变体选择窗口，并减轻不坚持治疗的影响。此外，我们还表明，与以恒定速率杀死细菌的免疫反应相比，一种在高细菌载量时降低杀菌能力而在低细菌载量时增加杀菌能力的免疫反应有时更可取。我们讨论了从这项研究中得出的预测和假设，以及如何通过实验对它们进行检验。
