Jung Paul P, Christian Nils, Kay Daniel P, Skupin Alexander, Linster Carole L
Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; National Center for Microscopy and Imaging Research, University of California San Diego, La Jolla, California, United States of America.
PLoS One. 2015 Mar 30;10(3):e0119807. doi: 10.1371/journal.pone.0119807. eCollection 2015.
In microorganisms, and more particularly in yeasts, a standard phenotyping approach consists in the analysis of fitness by growth rate determination in different conditions. One growth assay that combines high throughput with high resolution involves the generation of growth curves from 96-well plate microcultivations in thermostated and shaking plate readers. To push the throughput of this method to the next level, we have adapted it in this study to the use of 384-well plates. The values of the extracted growth parameters (lag time, doubling time and yield of biomass) correlated well between experiments carried out in 384-well plates as compared to 96-well plates or batch cultures, validating the higher-throughput approach for phenotypic screens. The method is not restricted to the use of the budding yeast Saccharomyces cerevisiae, as shown by consistent results for other species selected from the Hemiascomycete class. Furthermore, we used the 384-well plate microcultivations to develop and validate a higher-throughput assay for yeast Chronological Life Span (CLS), a parameter that is still commonly determined by a cumbersome method based on counting "Colony Forming Units". To accelerate analysis of the large datasets generated by the described growth and aging assays, we developed the freely available software tools GATHODE and CATHODE. These tools allow for semi-automatic determination of growth parameters and CLS behavior from typical plate reader output files. The described protocols and programs will increase the time- and cost-efficiency of a number of yeast-based systems genetics experiments as well as various types of screens.
在微生物中,尤其是在酵母中,一种标准的表型分析方法是通过测定不同条件下的生长速率来分析适应性。一种将高通量与高分辨率相结合的生长测定方法是在恒温摇床式酶标仪中通过96孔板微量培养生成生长曲线。为了将该方法的通量提升到更高水平,我们在本研究中对其进行了改进,使其适用于384孔板。与96孔板或分批培养相比,在384孔板中进行的实验所提取的生长参数(延迟期、倍增时间和生物量产量)值之间具有良好的相关性,这验证了用于表型筛选的高通量方法。该方法并不局限于使用出芽酵母酿酒酵母,从半子囊菌纲中选择的其他物种也得到了一致的结果。此外,我们利用384孔板微量培养开发并验证了一种用于酵母时序寿命(CLS)的高通量测定方法,该参数目前仍通常通过基于计数“菌落形成单位”的繁琐方法来确定。为了加速对所述生长和衰老测定产生的大量数据集的分析,我们开发了免费的软件工具GATHODE和CATHODE。这些工具可从典型的酶标仪输出文件中半自动确定生长参数和CLS行为。所描述的方案和程序将提高许多基于酵母的系统遗传学实验以及各种类型筛选的时间和成本效率。