Accelerated high-throughput imaging and phenotyping system for small organisms

被引:4
|
作者
Kose, Talha [1 ]
Lins, Tiago F. [1 ]
Wang, Jessie [2 ]
O'Brien, Anna M. [1 ,2 ,3 ]
Sinton, David [1 ]
Frederickson, Megan E. [2 ]
机构
[1] Univ Toronto, Dept Mech & Ind Engn, Toronto, ON, Canada
[2] Univ Toronto, Dept Ecol & Evolutionary Biol, Toronto, ON, Canada
[3] Univ New Hampshire, Dept Mol Cellular & Biomed Sci, Durham, NH USA
来源
PLOS ONE | 2023年 / 18卷 / 07期
基金
加拿大自然科学与工程研究理事会;
关键词
NITROGEN CONCENTRATION; STRESSORS; GROWTH; CORN;
D O I
10.1371/journal.pone.0287739
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Studying the complex web of interactions in biological communities requires large multifactorial experiments with sufficient statistical power. Automation tools reduce the time and labor associated with setup, data collection, and analysis in experiments that untangle these webs. We developed tools for high-throughput experimentation (HTE) in duckweeds, small aquatic plants that are amenable to autonomous experimental preparation and image-based phenotyping. We showcase the abilities of our HTE system in a study with 6,000 experimental units grown across 2,000 treatments. These automated tools facilitated the collection and analysis of time-resolved growth data, which revealed finer dynamics of plant-microbe interactions across environmental gradients. Altogether, our HTE system can run experiments with up to 11,520 experimental units and can be adapted for other small organisms.
引用
收藏
页数:10
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