Towards a Better Understanding of Microbial Community Dynamics through High-Throughput Cultivation and Data Integration

被引:11
|
作者
Faust, Karoline [1 ]
机构
[1] Katholieke Univ Leuven, Dept Microbiol Immunol & Transplantat, Lab Mol Bacteriol, Rega Inst, Leuven, Belgium
基金
欧洲研究理事会;
关键词
community models; data integration; high-throughput cultivation; microbial community dynamics; microbial systems biology;
D O I
10.1128/mSystems.00101-19
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
The investigation of microbial community dynamics is hampered by low resolution, a lack of control, and a small number of replicates. These deficiencies can be tackled with defined communities grown under well-controlled conditions in high-throughput automated cultivation devices. Besides delivering high-quality microbial community data, automated cultivation will also ease measurement of the basic parameters needed to parameterize mathematical models of microbial communities. Better experimental data will allow revisiting classical ecological questions, such as the impact of community structure on dynamics. In addition, such data will allow validation and comparison of community models and benchmarking of microbial data analysis software. In summary, high-throughput automated cultivation will lead to a deeper understanding of microbial community dynamics through better models and software.
引用
收藏
页数:4
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