PDF(Pubmed)
Abstract：
Extracellular bacterial metabolites have potential as markers of bacterial growth and resistance emergence but have not been evaluated in dynamic in vitro studies. We investigated the dynamic metabolomic footprint of a multidrug-resistant hypermutable Pseudomonas aeruginosa isolate exposed to ceftolozane/tazobactam as continuous infusion (4.5 g/day, 9 g/day) in a hollow-fiber infection model over 7-9 days in biological replicates (n = 5). Bacterial samples were collected at 0, 7, 23, 47, 71, 95, 143, 167, 191, and 215 h, the supernatant quenched, and extracellular metabolites extracted. Metabolites were analyzed via untargeted metabolomics, including hierarchical clustering and correlation with quantified total and resistant bacterial populations. The time-courses of five (of 1,921 detected) metabolites from enriched pathways were mathematically modeled. Absorbed L-arginine and secreted L-ornithine were highly correlated with the total bacterial population (r -0.79 and 0.82, respectively, P<0.0001). Ribose-5-phosphate, sedoheptulose-7-phosphate, and trehalose-6-phosphate correlated with the resistant subpopulation (0.64, 0.64, and 0.67, respectively, P<0.0001) and were likely secreted due to resistant growth overcoming oxidative and osmotic stress induced by ceftolozane/tazobactam. Using pharmacokinetic/pharmacodynamic-based transduction models, these metabolites were successfully modeled based on the total or resistant bacterial populations. The models well described the abundance of each metabolite across the differing time-course profiles of biological replicates, based on bacterial killing and, importantly, resistant regrowth. These proof-of-concept studies suggest that further exploration is warranted to determine the generalizability of these findings. The metabolites modeled here are not exclusive to bacteria. Future studies may use this approach to identify bacteria-specific metabolites correlating with resistance, which would ultimately be extremely useful for clinical translation.
摘要：
细胞外细菌代谢物具有作为细菌生长和抗性出现的标志物的潜力，但尚未在动态体外研究中进行评估。我们调查了连续输注头孢洛扎/他唑巴坦（4.5g/天，9g/天）在7-9天的中空纤维感染模型中进行生物学复制（n=5）。在0、7、23、47、71、95、143、167、191和215h收集细菌样品。淬灭的上清液，和提取的细胞外代谢物。通过非靶向代谢组学分析代谢物，包括分层聚类和与定量的总细菌和抗性细菌种群的相关性。对来自富集途径的五种（检测到的1,921种）代谢物的时间过程进行了数学建模。吸收的L-精氨酸和分泌的L-鸟氨酸与细菌总数高度相关（r分别为-0.79和0.82，P<0.0001)。核糖-5-磷酸,去核庚糖-7-磷酸，和海藻糖-6-磷酸与抗性亚群相关(分别为0.64、0.64和0.67，P<0.0001），并且可能是由于抵抗头孢特洛扎/他唑巴坦诱导的氧化和渗透胁迫的抗性生长而分泌的。使用基于药代动力学/药效学的转导模型，这些代谢物基于总细菌或耐药细菌种群成功建模.这些模型很好地描述了生物重复的不同时程曲线中每种代谢物的丰度，基于细菌杀灭，重要的是,抗性再生长。这些概念验证研究表明，需要进一步探索以确定这些发现的普遍性。这里建模的代谢物不是细菌独有的。未来的研究可能会使用这种方法来鉴定与耐药性相关的细菌特异性代谢物。这最终将对临床翻译非常有用。
