The E-coli molecular phenotype under different growth conditions

The E-coli molecular phenotype under different growth conditions
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DOI:
10.1038/srep45303
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发表时间:
2017-04-18
期刊:
影响因子:
4.6
通讯作者:
Wilke, Claus O.
Wilke, Claus O.
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Caglar, Mehmet U.;Houser, John R.;Wilke, Claus O.

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现代系统生物学需要广泛的,精心策划的细胞成分的测量,以响应不同的环境条件。虽然高通量方法使转录组学和蛋白质组学数据集广泛可及且相对经济,但在各种不同条件下对mRNA和蛋白质丰度的系统测量仍然相对罕见。在这里,我们展示了在34种不同条件下生长的大肠杆菌的详细的全基因组转录组学和蛋白质组学数据集。此外,我们通过中心碳代谢提供加倍时间和体内代谢通量的测量。我们控制生长培养基中钠和镁的浓度,并考虑四种不同的碳源葡萄糖、葡萄糖酸盐、乳酸盐和甘油。此外,样本在指数和平稳阶段都采取了,我们包括两个广泛的时间过程,多个样本在3小时和2周之间采取。我们发现指数相样品系统地不同于固定相样品,特别是在mRNA水平上。对不同碳源或盐胁迫的调控反应较为温和,但我们发现在葡萄糖酸盐和盐镁胁迫下的生长有许多差异表达的基因。我们的数据集为未来大肠杆菌基因调控、转录和翻译的计算建模提供了丰富的资源。
Modern systems biology requires extensive, carefully curated measurements of cellular components in response to different environmental conditions. While high-throughput methods have made transcriptomics and proteomics datasets widely accessible and relatively economical to generate, systematic measurements of both mRNA and protein abundances under a wide range of different conditions are still relatively rare. Here we present a detailed, genome-wide transcriptomics and proteomics dataset of E. coli grown under 34 different conditions. Additionally, we provide measurements of doubling times and in-vivo metabolic fluxes through the central carbon metabolism. We manipulate concentrations of sodium and magnesium in the growth media, and we consider four different carbon sources glucose, gluconate, lactate, and glycerol. Moreover, samples are taken both in exponential and stationary phase, and we include two extensive time-courses, with multiple samples taken between 3 hours and 2 weeks. We find that exponential-phase samples systematically differ from stationary-phase samples, in particular at the level of mRNA. Regulatory responses to different carbon sources or salt stresses are more moderate, but we find numerous differentially expressed genes for growth on gluconate and under salt and magnesium stress. Our data set provides a rich resource for future computational modeling of E. coli gene regulation, transcription, and translation.