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Polysome-profiling in small tissue samples

机译:小组织样品中的多血细胞谱

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Polysome-profiling is commonly used to study translatomes and applies laborious extraction of efficiently translated mRNA (associated with & 3 ribosomes) from a large volume across many fractions. This property makes polysome-profiling inconvenient for larger experimental designs or samples with low RNA amounts. To address this, we optimized a non-linear sucrose gradient which reproducibly enriches for efficiently translated mRNA in only one or two fractions, thereby reducing sample handling 5-10-fold. The technique generates polysomeassociated RNA with a quality reflecting the starting material and, when coupled with smart-seq2 singlecell RNA sequencing, translatomes in small tissues from biobanks can be obtained. Translatomes acquired using optimized non-linear gradients resemble those obtained with the standard approach employing linear gradients. Polysome-profiling using optimized non-linear gradients in serum starved HCT-116 cells with or without p53 showed that p53 status associates with changes in mRNA abundance and translational efficiency leading to changes in protein levels. Moreover, p53 status also induced translational buffering whereby changes in mRNA levels are buffered at the level of mRNA translation. Thus, here we present a polysome-profiling technique applicable to large study designs, primary cells and frozen tissue samples such as those collected in biobanks.
机译:多核糖体分析通常用于研究translatomes并施加有效地翻译mRNA的费力的提取(与&安培相关联; 3个核糖体; GT)由跨许多级分大的体积。这种性质使得对于较大的实验设计或具有低量的RNA样品多核糖体仿形不方便。为了解决这个问题,我们进行了优化的非线性蔗糖梯度仅在一个或两个级分,其可再现丰富了有效翻译的mRNA,从而降低了样品处理5-10倍。该技术产生polysomeassociated RNA与质量反映起始原料,当与智能SEQ2 singlecell RNA测序耦合,能够获得在小组织translatomes从生物库。使用优化的非线性梯度获取Translatomes类似于与采用线性梯度的标准方法获得的那些。多核糖体仿形在血清饥饿HCT-116细胞用或不用p53的使用优化的非线性梯度表明,p53状态与相关联的mRNA丰度和翻译效率的变化,导致在蛋白质水平的变化。此外,p53状态也诱导平移缓冲由此在mRNA水平的变化在mRNA翻译水平被缓冲。因此,这里我们提出适用于大的研究设计,原代细胞和冷冻的组织样品,例如在生物库收集多核糖体仿形技术。

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