Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, NC, USA.
Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, NC, USA; Marsico Lung Institute, University of North Carolina at Chapel Hill, NC, USA.
Curr Opin Microbiol. 2018 Apr;42:19-24. doi: 10.1016/j.mib.2017.09.007. Epub 2017 Oct 6.
Accurate prediction of antimicrobial efficacy is essential for successful treatment of bacterial infection. Beyond genetically encoded mechanisms of antibiotic resistance, the determinants of antibiotic susceptibility during infection remain poorly understood, and treatment failure is common. Traditional antibiotic susceptibility testing fails to account for extrinsic determinants of antibiotic susceptibility present in the complex infection environment and is therefore a poor predictor of antibiotic treatment outcome. Here we discuss how host-pathogen interaction, microbial interspecies interaction, and metabolic heterogeneity contribute to the success or failure of antibiotic therapy. Consideration of these factors during the treatment of disease will improve our ability to successfully resolve recalcitrant bacterial infection and improve patient health.
准确预测抗菌疗效对于成功治疗细菌感染至关重要。除了遗传编码的抗生素耐药机制外,感染期间抗生素敏感性的决定因素仍知之甚少,且治疗失败较为常见。传统的抗生素药敏试验未能考虑到感染环境中存在的抗生素敏感性的外在决定因素,因此对抗生素治疗结果的预测能力较差。在这里,我们讨论了宿主-病原体相互作用、微生物种间相互作用和代谢异质性如何影响抗生素治疗的成败。在治疗疾病时考虑这些因素将提高我们成功解决难治性细菌感染并改善患者健康的能力。