Predicting the Dynamics and Heterogeneity of Genomic DNA Content within Bacterial Populations across Variable Growth Regimes.
Predicting the Dynamics and Heterogeneity of Genomic DNA Content within Bacterial Populations across Variable Growth Regimes.
复制标题
预测不同生长机制下细菌群体内基因组 DNA 含量的动态和异质性。
DOI：
10.1021/acssynbio.5b00217
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发表时间：
2017
影响因子：
4.7
通讯作者：
Du Lac M
中科院分区：
文献类型：
--
作者：
Du Lac M
对于微生物合成生物学中的许多应用，优化所需功能需要仔细调整各种基因的表达程度。预测此类效应或解释典型表征实验的一项挑战是在大肠杆菌等细菌中。在大肠杆菌中，基因组拷贝数在不同阶段和生长速度中差异很大，这也影响基因从不同位点表达的方式和时间。虽然这种现象在机械层面上得到了相对较好的理解，但我们对此类过程的定量理解本质上仅限于理想的指数增长。相比之下，常见的实验现象，例如异质培养基上的生长、代谢适应和氧气限制，都会导致与理想指数生长的显着偏差，特别是当培养物接近进行工业生物制造甚至常规筛选实验的更高密度时。为了满足预测和解释基因剂量如何影响指数增长之外的细胞功能的需求，我们在此报告了一种新颖的建模策略，该策略利用基于代理的模拟和高性能计算来稳健地预测不同生长状态下细菌群体内基因组 DNA 含量的动态和异质性。我们表明，通过将常规实验数据（例如光密度时间序列）输入到我们的异质多相生长模拟器中，我们可以预测一系列非指数生长条件下的基因组 DNA 分布。这种建模策略为合成生物学家评估基因组 DNA 含量和异质性在影响现有或工程微生物功能性能方面的作用提供了重要的进步。
For many applications in microbial synthetic biology, optimizing a desired function requires careful tuning of the degree to which various genes are expressed. One challenge for predicting such effects or interpreting typical characterization experiments is that in bacteria such asE. coli, genome copy number varies widely across different phases and rates of growth, which also impacts how and when genes are expressed from different loci. While such phenomena are relatively well-understood at a mechanistic level, our quantitative understanding of such processes is essentially limited to ideal exponential growth. In contrast, common experimental phenomena such as growth on heterogeneous media, metabolic adaptation, and oxygen restriction all cause substantial deviations from ideal exponential growth, particularly as cultures approach the higher densities at which industrial biomanufacturing and even routine screening experiments are conducted. To meet the need for predicting and explaining how gene dosage impacts cellular functions outside of exponential growth, we here report a novel modeling strategy that leverages agent-based simulation and high performance computing to robustly predict the dynamics and heterogeneity of genomic DNA content within bacterial populations across variable growth regimes. We show that by feeding routine experimental data, such as optical density time series, into our heterogeneous multiphasic growth simulator, we can predict genomic DNA distributions over a range of nonexponential growth conditions. This modeling strategy provides an important advance in the ability of synthetic biologists to evaluate the role of genomic DNA content and heterogeneity in affecting the performance of existing or engineered microbial functions.
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影响因子：
5.2
作者：
Robert L
通讯作者：
Robert L
FtsK 主动分离大肠杆菌中的姐妹染色体
DOI：
--
发表时间：
2013
影响因子：
11.1
作者：
Mathieu Stouf;J. Meile;F. Cornet
通讯作者：
F. Cornet
影响因子：
3.7
作者：
Stokke C;Flåtten I;Skarstad K
通讯作者：
Skarstad K
DOI：
10.1099/00221287-18-2-382
发表时间：
1958
期刊：
Journal of general microbiology
影响因子：
--
作者：
E. Powell
通讯作者：
E. Powell
影响因子：
4.8
作者：
Khan, Sharik R.;Kuzminov, Andrei
通讯作者：
Kuzminov, Andrei