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YODA：一款用于促进芽殖酵母中时序寿命、生长速率和存活率高通量分析的软件。

YODA: software to facilitate high-throughput analysis of chronological life span, growth rate, and survival in budding yeast.

机构信息

Department of Pathology, University of Washington, Seattle, WA 98195, USA.

出版信息

BMC Bioinformatics. 2010 Mar 18;11:141. doi: 10.1186/1471-2105-11-141.

DOI:10.1186/1471-2105-11-141
PMID:20298554
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2850362/
Abstract

BACKGROUND

The budding yeast Saccharomyces cerevisiae is one of the most widely studied model organisms in aging-related science. Although several genetic modifiers of yeast longevity have been identified, the utility of this system for longevity studies has been limited by a lack of high-throughput assays for quantitatively measuring survival of individual yeast cells during aging.

RESULTS

Here we describe the Yeast Outgrowth Data Analyzer (YODA), an automated system for analyzing population survival of yeast cells based on the kinetics of outgrowth measured by optical density over time. YODA has been designed specifically for quantification of yeast chronological life span, but can also be used to quantify growth rate and survival of yeast cells in response to a variety of different conditions, including temperature, nutritional composition of the growth media, and chemical treatments. YODA is optimized for use with a Bioscreen C MBR shaker/incubator/plate reader, but is also amenable to use with any standard plate reader or spectrophotometer.

CONCLUSIONS

We estimate that use of YODA as described here reduces the effort and resources required to measure chronological life span and analyze the resulting data by at least 15-fold.

摘要

背景

budding 酵母酿酒酵母是衰老相关科学中研究最广泛的模式生物之一。尽管已经确定了几种延长酵母寿命的遗传修饰物，但由于缺乏高通量测定个体酵母细胞在衰老过程中存活的方法，该系统在寿命研究中的应用受到限制。

结果

在这里，我们描述了 Yeast Outgrowth Data Analyzer（YODA），这是一种基于随时间推移的吸光度测量来分析酵母细胞群体存活的自动化系统。YODA 是专门为定量测定酵母chronological life span 而设计的，但也可用于定量测定酵母细胞在各种不同条件下的生长速率和存活能力，包括温度、生长培养基的营养成分和化学处理。YODA 经过优化可与 Bioscreen C MBR 摇床/孵育器/平板读数器一起使用，但也可与任何标准平板读数器或分光光度计一起使用。

结论

我们估计，按照这里的描述使用 YODA 至少可以减少 15 倍测量 chronological life span 所需的工作量和资源，并分析由此产生的数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/0640c4aab6d8/1471-2105-11-141-7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/3bbf972c8305/1471-2105-11-141-1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/310c1db08c22/1471-2105-11-141-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/94ed151a6b17/1471-2105-11-141-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/0640c4aab6d8/1471-2105-11-141-7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/3bbf972c8305/1471-2105-11-141-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/f1baf6487715/1471-2105-11-141-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/4680b39df6b2/1471-2105-11-141-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/b4bee035b5be/1471-2105-11-141-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/310c1db08c22/1471-2105-11-141-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/94ed151a6b17/1471-2105-11-141-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7e/2850362/0640c4aab6d8/1471-2105-11-141-7.jpg

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