In vivo-like nearest neighbor parameters improve prediction of fractional RNA base-pairing in cells.
In vivo-like nearest neighbor parameters improve prediction of fractional RNA base-pairing in cells.
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DOI：
10.1093/nar/gkad807
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发表时间：
2023-11-10
影响因子：
14.9
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中科院分区：
文献类型：
--
作者：
我们在Eco 80人工细胞质中进行了RNA稳定性的热力学分析，该细胞质模拟体内条件，并将其与mRNA的转录组范围探测进行了比较。Eco 80含有80%的大肠杆菌代谢物，具有生物浓度的金属离子，包括2 mM游离Mg 2+和29 mM代谢物螯合Mg 2+。利用双折射检测结合等温线（FDBI）对24个RNA螺旋进行热力学分析，发现这些螺旋的平均稳定性为-12.3 kcal/mol，稳定性差ΔΔ Go 37 <$1 kcal/mol。FDBI数据用于确定一组Watson-Crick自由能最近邻参数（NNPs），这表明Eco 80降低了三个NNPs的稳定性。该信息用于使用RNAstructure包调整NN模型。体内调整对体外和计算机模拟确定的RNA二级结构的预测影响很小，但显著改善了E.大肠杆菌，作为基准与我们的体内DMS和EDC RNA化学探测数据。总之，我们对RNA螺旋的热力学和化学探测分析表明，RNA二级结构在细胞中的稳定性低于人工稳定的体外缓冲液条件。
We conducted a thermodynamic analysis of RNA stability in Eco80 artificial cytoplasm, which mimics in vivo conditions, and compared it to transcriptome-wide probing of mRNA. Eco80 contains 80% of Escherichia coli metabolites, with biological concentrations of metal ions, including 2 mM free Mg2+ and 29 mM metabolite-chelated Mg2+. Fluorescence-detected binding isotherms (FDBI) were used to conduct a thermodynamic analysis of 24 RNA helices and found that these helices, which have an average stability of –12.3 kcal/mol, are less stable by ΔΔGo37 ∼1 kcal/mol. The FDBI data was used to determine a set of Watson–Crick free energy nearest neighbor parameters (NNPs), which revealed that Eco80 reduces the stability of three NNPs. This information was used to adjust the NN model using the RNAstructure package. The in vivo-like adjustments have minimal effects on the prediction of RNA secondary structures determined in vitro and in silico, but markedly improve prediction of fractional RNA base pairing in E. coli, as benchmarked with our in vivo DMS and EDC RNA chemical probing data. In summary, our thermodynamic and chemical probing analyses of RNA helices indicate that RNA secondary structures are less stable in cells than in artificially stable in vitro buffer conditions.
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影响因子：
16.6
作者：
Lan TCT;Allan MF;Malsick LE;Woo JZ;Zhu C;Zhang F;Khandwala S;Nyeo SSY;Sun Y;Guo JU;Bathe M;Näär A;Griffiths A;Rouskin S
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Rouskin S
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Maksimova EM;Korepanov AP;Kravchenko OV;Baymukhametov TN;Myasnikov AG;Vassilenko KS;Afonina ZA;Stolboushkina EA
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Stolboushkina EA
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通讯作者：
Pielak, Gary J.
影响因子：
14.9
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Griffiths-Jones, S;Bateman, A;Eddy, SR
通讯作者：
Eddy, SR
影响因子：
6.8
作者：
Gutell, RR;Lee, JC;Cannone, JJ
通讯作者：
Cannone, JJ