Bento Clara M, Gomes Maria Salomé, Silva Tânia
I3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal.
IBMC-Instituto de Biologia Molecular e Celular, Universidade do Porto, 4200-135 Porto, Portugal.
Microorganisms. 2021 Dec 10;9(12):2562. doi: 10.3390/microorganisms9122562.
The increasing resistance of infectious agents to available drugs urges the continuous and rapid development of new and more efficient treatment options. This process, in turn, requires accurate and high-throughput techniques for antimicrobials' testing. Conventional methods of drug susceptibility testing (DST) are reliable and standardized by competent entities and have been thoroughly applied to a wide range of microorganisms. However, they require much manual work and time, especially in the case of slow-growing organisms, such as mycobacteria. Aiming at a better prediction of the clinical efficacy of new drugs, in vitro infection models have evolved to closely mimic the environment that microorganisms experience inside the host. Automated methods allow in vitro DST on a big scale, and they can integrate models that recreate the interactions that the bacteria establish with host cells in vivo. Nonetheless, they are expensive and require a high level of expertise, which makes them still not applicable to routine laboratory work. In this review, we discuss conventional DST methods and how they should be used as a first screen to select active compounds. We also highlight their limitations and how they can be overcome by more complex and sophisticated in vitro models that reflect the dynamics present in the host during infection. Special attention is given to mycobacteria, which are simultaneously difficult to treat and especially challenging to study in the context of DST.
感染因子对现有药物的耐药性不断增加，促使人们持续快速地开发新的、更有效的治疗方案。而这一过程反过来又需要准确且高通量的抗菌药物检测技术。传统的药敏试验（DST）方法可靠且已由权威机构标准化，并且已广泛应用于多种微生物。然而，它们需要大量的人工操作和时间，尤其是对于生长缓慢的微生物，如分枝杆菌。为了更好地预测新药的临床疗效，体外感染模型已经发展到能够紧密模拟微生物在宿主体内所处的环境。自动化方法允许大规模进行体外DST，并且可以整合能够重现细菌在体内与宿主细胞建立的相互作用的模型。尽管如此，它们成本高昂且需要高水平的专业知识，这使得它们仍然不适用于常规实验室工作。在这篇综述中，我们讨论传统的DST方法以及应如何将其用作筛选活性化合物的初步手段。我们还强调了它们的局限性以及如何通过更复杂、更精密的体外模型来克服这些局限性，这些模型能够反映感染期间宿主体内的动态变化。我们特别关注分枝杆菌，它们既难以治疗，又在DST背景下特别具有研究挑战性。
