Difference in persistent tuberculosis bacteria between in vitro and sputum from patients: implications for translational predictions.
Difference in persistent tuberculosis bacteria between in vitro and sputum from patients: implications for translational predictions.
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DOI：
10.1038/s41598-020-72472-y
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发表时间：
2020-09-23
影响因子：
4.6
通讯作者：
Simonsson USH
中科院分区：
文献类型：
--
作者：
Faraj A;Clewe O;Svensson RJ;Mukamolova GV;Barer MR;Simonsson USH
本研究旨在调查肺结核患者痰液中持久性细菌的数量与体外细菌的数量，并提出一种基于模型的方法来解释这种潜在差异。痰涂片阳性患者（n = 25）在化疗开始前提供痰液样本。用常规琼脂集落形成单位（CFU）和最大可能数（MPN）定量检测补充Rpf的细胞数。持久性细菌被假定为MPNrpf和CFU之间的差异。使用不同的基于模型的方法定量体外和化疗前人痰液之间持久性细菌的差异。痰液中的持久性细菌为体外水平的17%，表明表型耐药性存在差异，而细菌亚群的增殖没有差异。临床试验模拟显示，如果预测药物应答时忽略表型耐药差异，则使用体外临床前疗效信息在IIa期环境中预测MPNrpf下降2个对数的时间将延长近3天。在体外和人类化疗前发现的表型差异可能对翻译工作有影响，但可以使用基于模型的方法将体外转化为人类药物反应。
This study aimed to investigate the number of persistent bacteria in sputum from tuberculosis patients compared to in vitro and to suggest a model-based approach for accounting for the potential difference. Sputum smear positive patients (n = 25) provided sputum samples prior to onset of chemotherapy. The number of cells detected by conventional agar colony forming unit (CFU) and most probable number (MPN) with Rpf supplementation were quantified. Persistent bacteria was assumed to be the difference between MPNrpf and CFU. The difference in persistent bacteria between in vitro and human sputum prior to chemotherapy was quantified using different model-based approaches. The persistent bacteria in sputum was 17% of the in vitro levels, suggesting a difference in phenotypic resistance, whereas no difference was found for multiplying bacterial subpopulations. Clinical trial simulations showed that the predicted time to 2 log fall in MPNrpf in a Phase 2a setting using in vitro pre-clinical efficacy information, would be almost 3 days longer if drug response was predicted ignoring the difference in phenotypic resistance. The discovered phenotypic differences between in vitro and humans prior to chemotherapy could have implications on translational efforts but can be accounted for using a model-based approach for translating in vitro to human drug response.
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