Hydrophobicity and charge shape cellular metabolite concentrations.
Hydrophobicity and charge shape cellular metabolite concentrations.
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DOI：
10.1371/journal.pcbi.1002166
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发表时间：
2011-10
影响因子：
4.3
通讯作者：
Milo R
中科院分区：
文献类型：
--
作者：
Bar-Even A;Noor E;Flamholz A;Buescher JM;Milo R
是什么决定了活细胞内代谢物的浓度？除了特定的代谢和酶学考虑之外，是否有影响其价值的全球趋势？我们假设代谢物的理化性质在很大程度上影响其体内浓度。最近实现的同时测量多种代谢物浓度的实验能力使得检验这一假设成为可能。在这里，我们分析了最近获得的大肠杆菌、酿酒酵母、枯草芽孢杆菌和人类代谢物浓度的数据集。总体而言，这些数据集包含 20 多种条件，每个条件包含数十种 (28-108) 个同时测量的代谢物。我们测试了与各种物理化学性质的相关性，发现带电原子的数量、非极性表面积、亲脂性和溶解度始终与浓度相关。在大多数数据集中，这些特性之一的变化会导致代谢物浓度增加约 100 倍。我们发现，在最可靠、最全面的数据集中，非极性表面积和带电原子数量几乎占浓度变化的一半。分析特定的代谢物组，例如氨基酸或磷酸化核苷酸，甚至揭示了浓度对疏水性的更高依赖性。我们建议这些发现可以通过对代谢物浓度施加的进化限制来解释，并讨论可以解释它们的可能的选择压力。这些包括减少溶质通过脂质膜的渗漏、避免有害的聚集体以及减少非特异性疏水结合。通过强调代谢途径的全球限制，未来的研究可以揭示生化进化的各个方面以及限制代谢工程工作的化学限制。是什么决定了活细胞内代谢物的特性和浓度？这个问题的第一部分引起了很多关注。人们发现生物体在质量上更喜欢亲水性和带电的代谢物，这种现象被解释为当代和古代新陈代谢所施加的限制的结果。然而，在所使用的代谢物中，从未对定量偏好进行系统分析。在这里，我们使用最全面的代谢物浓度数据集来探索此类趋势。我们发现，在各种生物体和生长条件下，活细胞将非极性、不带电荷的代谢物的浓度降至最低。更具体地说，代谢物的疏水性使浓度平均改变两个数量级，并解释了细胞内代谢物浓度变化的一半。我们认为这可以归因于避免非特异性疏水效应的进化压力：水环境中的疏水表面倾向于粘附到其他疏水表面。我们的研究结果揭示了活细胞内部构成的进化，并有助于建立支持合成生物学和代谢工程工作的代谢模型。
What governs the concentrations of metabolites within living cells? Beyond specific metabolic and enzymatic considerations, are there global trends that affect their values? We hypothesize that the physico-chemical properties of metabolites considerably affect their in-vivo concentrations. The recently achieved experimental capability to measure the concentrations of many metabolites simultaneously has made the testing of this hypothesis possible. Here, we analyze such recently available data sets of metabolite concentrations within E. coli, S. cerevisiae, B. subtilis and human. Overall, these data sets encompass more than twenty conditions, each containing dozens (28-108) of simultaneously measured metabolites. We test for correlations with various physico-chemical properties and find that the number of charged atoms, non-polar surface area, lipophilicity and solubility consistently correlate with concentration. In most data sets, a change in one of these properties elicits a ∼100 fold increase in metabolite concentrations. We find that the non-polar surface area and number of charged atoms account for almost half of the variation in concentrations in the most reliable and comprehensive data set. Analyzing specific groups of metabolites, such as amino-acids or phosphorylated nucleotides, reveals even a higher dependence of concentration on hydrophobicity. We suggest that these findings can be explained by evolutionary constraints imposed on metabolite concentrations and discuss possible selective pressures that can account for them. These include the reduction of solute leakage through the lipid membrane, avoidance of deleterious aggregates and reduction of non-specific hydrophobic binding. By highlighting the global constraints imposed on metabolic pathways, future research could shed light onto aspects of biochemical evolution and the chemical constraints that bound metabolic engineering efforts. What governs the identity and concentrations of metabolites within living cells? The first part of this question has received much attention. Organisms were found to qualitatively prefer hydrophilic and charged metabolites, a phenomenon that was explained to be a result of constraints imposed by contemporary as well as archaic metabolism. However, among the metabolites that are used, a quantitative preference has never been analyzed systematically. Here we use the most comprehensive data sets of metabolite concentrations available to explore such trends. We find that in various organisms and growth conditions, living cells minimize the concentrations of non-polar, un-charged metabolites. More specifically, metabolites' hydrophobicity alters concentrations by two orders of magnitudes on average and explains up to half of the variation of metabolite concentrations within cells. We suggest that this can be attributed to an evolutionary pressure to avoid an unspecific hydrophobic effect: the preference of hydrophobic surfaces in an aqueous environment to adhere to other hydrophobic surfaces. Our findings shed light on the evolution of the internal makeup of living cells and can assist in establishing metabolic models that support synthetic biology and metabolic engineering efforts.
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影响因子：
56.9
作者：
Ishii, Nobuyoshi;Nakahigashi, Kenji;Tomita, Masaru
通讯作者：
Tomita, Masaru
影响因子：
--
作者：
O'Boyle NM;Morley C;Hutchison GR
通讯作者：
Hutchison GR
影响因子：
6.8
作者：
Hopkins, AL;Mason, JS;Overington, JP
通讯作者：
Overington, JP
DOI：
10.1073/pnas.71.8.2925
发表时间：
1974-01-01
影响因子：
11.1
作者：
REYNOLDS, JA;GILBERT, DB;TANFORD, C
通讯作者：
TANFORD, C
影响因子：
5.6
作者：
RICHMOND, TJ
通讯作者：
RICHMOND, TJ