Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale.
Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale.
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DOI：
10.1534/g3.116.032342
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发表时间：
2016-09-08
期刊：
影响因子：
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通讯作者：
Blomberg A
中科院分区：
文献类型：
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作者：
Zackrisson M;Hallin J;Ottosson LG;Dahl P;Fernandez-Parada E;Ländström E;Fernandez-Ricaud L;Kaferle P;Skyman A;Stenberg S;Omholt S;Petrovič U;Warringer J;Blomberg A
绘制大量个体特征图谱的能力——表现学——远远落后于基因组学的爆炸性发展。对于微生物来说，生长的估计是关键的表型，因为它与适应性有关。我们引入了一个自动化的微生物表型组学框架，以前所未有的规模提供准确，精确和高度解决的生长表型。通过引入透射扫描硬件和软件技术，频繁获取精确的种群规模测量，从生长曲线中提取种群增长率，以及通过参考表面归一化消除空间偏差，取得了进展。我们的原型装置可以自动记录和分析近10万条生长曲线。我们通过扩展和细化面包师酵母中已知的盐防御生物学来证明这种方法的力量。引入的框架代表了微生物表型组学的重大进步，为广泛的个体队列提供了高质量的数据，并产生了大量的标准化表型组学数据库
The capacity to map traits over large cohorts of individuals—phenomics—lags far behind the explosive development in genomics. For microbes, the estimation of growth is the key phenotype because of its link to fitness. We introduce an automated microbial phenomics framework that delivers accurate, precise, and highly resolved growth phenotypes at an unprecedented scale. Advancements were achieved through the introduction of transmissive scanning hardware and software technology, frequent acquisition of exact colony population size measurements, extraction of population growth rates from growth curves, and removal of spatial bias by reference-surface normalization. Our prototype arrangement automatically records and analyzes close to 100,000 growth curves in parallel. We demonstrate the power of the approach by extending and nuancing the known salt-defense biology in baker’s yeast. The introduced framework represents a major advance in microbial phenomics by providing high-quality data for extensive cohorts of individuals and generating well-populated and standardized phenomics databases