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高通量分析噬菌体菌株间的生长差异。

High-throughput analysis of growth differences among phage strains.

机构信息

Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA.

出版信息

J Microbiol Methods. 2012 Jan;88(1):117-21. doi: 10.1016/j.mimet.2011.10.020. Epub 2011 Nov 12.

Abstract

Although methods such as spectrophotometry are useful for identifying growth differences among bacterial strains, it is currently difficult to similarly determine whether bacteriophage strains differ in growth using high throughput methods. Here we use automated spectrophotometry to develop an in vitro method for indirectly distinguishing fitness (growth) differences among virus strains, based on direct measures of their infected bacterial hosts. We used computer simulations of a mathematical model for phage growth to predict which features of bacterial growth curves were best associated with differences in growth among phage strains. We then tested these predictions using the in vitro method to confirm which of the inferred viral growth traits best reflected known fitness differences among genotypes of the RNA phage phi-6, when infecting a Pseudomonas syringae host. Results showed that the inferred phage trait of time-to-extinction (time required to drive bacterial density below detectable optical density) reliably correlated with genotype rankings based on absolute fitness (phage titer per ml). These data suggested that the high-throughput analysis was valuable for identifying growth differences among virus strains, and that the method may be especially useful for high throughput analyses of fitness differences among phage strains cultured and/or evolved in liquid (unstructured) environments.

摘要

尽管分光光度法等方法可用于识别细菌菌株之间的生长差异,但目前很难使用高通量方法类似地确定噬菌体菌株在生长方面是否存在差异。在这里,我们使用自动化分光光度法,根据受感染的细菌宿主的直接测量值,开发了一种间接区分病毒株之间适应性(生长)差异的体外方法。我们使用噬菌体生长的数学模型的计算机模拟来预测哪些细菌生长曲线的特征与噬菌体株之间的生长差异最相关。然后,我们使用体外方法来验证这些预测,以确认在感染丁香假单胞菌宿主时,推断出的噬菌体生长特征中哪些最能反映 RNA 噬菌体 phi-6 基因型之间的已知适应性差异。结果表明,推断出的噬菌体灭绝时间(将细菌密度降低到可检测的光密度以下所需的时间)与基于绝对适应性(每毫升噬菌体滴度)的基因型排名可靠相关。这些数据表明,高通量分析可用于识别病毒株之间的生长差异,并且该方法可能特别适用于在液体(无结构)环境中培养和/或进化的噬菌体株之间适应性差异的高通量分析。

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