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高通量分析抗疟药物敏感性数据的世界抗疟研究网络(WWARN)的体外分析和报告工具。

High-throughput analysis of antimalarial susceptibility data by the WorldWide Antimalarial Resistance Network (WWARN) in vitro analysis and reporting tool.

机构信息

WorldWide Antimalarial Resistance Network (WWARN), Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Churchill Hospital, Oxford, United Kingdom.

出版信息

Antimicrob Agents Chemother. 2013 Jul;57(7):3121-30. doi: 10.1128/AAC.02350-12. Epub 2013 Apr 22.

Abstract

Assessment of in vitro susceptibility is a fundamental component of antimalarial surveillance studies, but wide variations in the measurement of parasite growth and the calculation of inhibitory constants make comparisons of data from different laboratories difficult. Here we describe a Web-based, high-throughput in vitro analysis and reporting tool (IVART) generating inhibitory constants for large data sets. Fourteen primary data sets examining laboratory-determined susceptibility to artemisinin derivatives and artemisinin combination therapy partner drugs were collated from 11 laboratories. Drug concentrations associated with half-maximal inhibition of growth (IC50s) were determined by a modified sigmoid Emax model-fitting algorithm, allowing standardized analysis of 7,350 concentration-inhibition assays involving 1,592 isolates. Examination of concentration-inhibition data revealed evidence of apparent paradoxical growth at high concentrations of nonartemisinin drugs, supporting amendment of the method for calculating the maximal drug effect in each assay. Criteria for defining more-reliable IC50s based on estimated confidence intervals and growth ratios improved correlation coefficients for the drug pairs mefloquine-quinine and chloroquine-desethylamodiaquine in 9 of 11 and 8 of 8 data sets, respectively. Further analysis showed that maximal drug inhibition was higher for artemisinins than for other drugs, particularly in ELISA (enzyme-linked immunosorbent assay)-based assays, a finding consistent with the earlier onset of action of these drugs in the parasite life cycle. This is the first high-throughput analytical approach to apply consistent constraints and reliability criteria to large, diverse antimalarial susceptibility data sets. The data also illustrate the distinct biological properties of artemisinins and underline the need to apply more sensitive approaches to assessing in vitro susceptibility to these drugs.

摘要

体外药敏评估是抗疟监测研究的基本组成部分,但寄生虫生长的测量和抑制常数的计算方法存在广泛差异,使得不同实验室的数据比较变得困难。在这里,我们描述了一个基于网络的高通量体外分析和报告工具(IVART),用于生成大量数据集的抑制常数。从 11 个实验室收集了 14 个检查实验室确定的青蒿素衍生物和青蒿素联合治疗伙伴药物敏感性的原始数据集。通过改良的 sigmoid Emax 模型拟合算法确定与生长抑制半最大值相关的药物浓度(IC50),允许标准化分析涉及 1592 个分离株的 7350 个浓度抑制测定。对浓度抑制数据的检查表明,在非青蒿素药物的高浓度下存在明显的反常生长的证据,支持在每个测定中计算最大药物效应的方法的修正。基于估计置信区间和生长比定义更可靠的 IC50 的标准,分别提高了 11 个和 8 个数据集中 9 个和 8 个药物对(甲氟喹-奎宁和氯喹-去乙基阿莫地喹)的相关系数。进一步的分析表明,青蒿素类药物的最大药物抑制作用高于其他药物,特别是在 ELISA(酶联免疫吸附测定)基础的测定中,这一发现与这些药物在寄生虫生命周期中较早的作用一致。这是第一个应用一致的约束和可靠性标准来处理大型、多样化的抗疟药物敏感性数据集的高通量分析方法。这些数据还说明了青蒿素类药物的独特生物学特性,并强调需要应用更敏感的方法来评估这些药物的体外敏感性。

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