Peroxisomal lactate dehydrogenase is generated by translational readthrough in mammals.
Peroxisomal lactate dehydrogenase is generated by translational readthrough in mammals.
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DOI：
10.7554/elife.03640
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发表时间：
2014-09-23
期刊：
影响因子：
7.7
通讯作者：
Thoms S
中科院分区：
文献类型：
--
作者：
Schueren F;Lingner T;George R;Hofhuis J;Dickel C;Gärtner J;Thoms S
翻译通读产生C-末端延伸超过终止密码子的低丰度蛋白质。为了鉴定功能性翻译通读，我们通过计算机模拟的新回归模型估计了人类基因组的所有终止密码子背景的通读倾向（RTP），通过使用该模型鉴定了高RTP的核苷酸共有基序，并使用过氧化物酶体靶向信号类型1（PTS 1）的新预测因子分析了计算机模拟的所有通读延伸。乳酸脱氢酶B（LDHB）显示出最高的RTP和PTS 1组合概率。实验表明，至少有1.6%的总细胞LDHB是针对过氧化物酶体的保守隐藏的PTS 1。通读延伸的乳酸脱氢酶亚基LDHBx也可以将另一种LDH亚基LDHA共输入过氧化物酶体中。过氧化物酶体LDH在哺乳动物中是保守的，并且可能有助于过氧化物酶体中的氧化还原当量再生。DOI：http://dx.doi.org/10.7554/eLife.03640.001氨基酸是蛋白质的组成部分，蛋白质中氨基酸的顺序由信使RNA分子中“密码子”出现的顺序决定。大多数密码子代表特定的氨基酸，但也有三个终止密码子用于标记蛋白质的末端。当将信使RNA分子“翻译”成蛋白质的细胞机器遇到终止密码子时，它会停止并释放完整的蛋白质。然而，有时终止密码子并不被解释为终止信号，信使RNA分子的翻译会继续，直到遇到另一个终止密码子。这个过程称为通读。一些生物，特别是病毒和真菌，使用通读来产生比它们的基因组所允许的更广泛的蛋白质。虽然通读也发生在高等生物如哺乳动物中，但尚不清楚产生的蛋白质是否执行原始蛋白质不执行的额外功能。许多因素影响mRNA模板翻译时是否发生通读。例如，三个终止密码子中的每一个都有不同的终止信号被误解的可能性，并且终止密码子周围的mRNA序列也会影响通读的可能性。Schueren等人开发了一个计算模型，估计这种形式的翻译通读在人类基因组中有多常见。该模型基于终止密码子本身和周围mRNA序列的同一性。然后将该模型与另一个模型相结合，该模型识别了靶向细胞内称为过氧化物酶体的结构的蛋白质，该结构是许多必要的能量释放反应发生的地方。组合模型使Schueren等人能够鉴定在过氧化物酶体中执行功能并且可能通过通读形成的蛋白质。结合模型提出了一种蛋白质，它是乳酸脱氢酶的一部分：一种加速化学反应的酶，对细胞产生能量很重要。以前在过氧化物酶体中发现了低水平的乳酸脱氢酶，尽管它显然缺乏蛋白质进入过氧化物酶体所需的特定氨基酸序列。然而，Schueren等人通过实验证实，模型识别的乳酸脱氢酶组分确实发生了通读，揭示了它包含一个“隐藏的”过氧化物酶体靶向区域。此外，当更多的翻译通读发生时，在过氧化物酶体中发现更多的乳酸脱氢酶。乳酸脱氢酶进入过氧化物酶体的这种不寻常的方式是细胞如何优化基因组和信使RNA中编码的遗传信息的一个例子。翻译通读总是确保一定比例的乳酸脱氢酶将被带到过氧化物酶体。这里开发的计算模型将是一个有价值的工具，以确定其他此类蛋白质产生的基因组，包括人类基因组和其他物种。DOI：http://dx.doi.org/10.7554/eLife.03640.002网站
Translational readthrough gives rise to low abundance proteins with C-terminal extensions beyond the stop codon. To identify functional translational readthrough, we estimated the readthrough propensity (RTP) of all stop codon contexts of the human genome by a new regression model in silico, identified a nucleotide consensus motif for high RTP by using this model, and analyzed all readthrough extensions in silico with a new predictor for peroxisomal targeting signal type 1 (PTS1). Lactate dehydrogenase B (LDHB) showed the highest combined RTP and PTS1 probability. Experimentally we show that at least 1.6% of the total cellular LDHB is targeted to the peroxisome by a conserved hidden PTS1. The readthrough-extended lactate dehydrogenase subunit LDHBx can also co-import LDHA, the other LDH subunit, into peroxisomes. Peroxisomal LDH is conserved in mammals and likely contributes to redox equivalent regeneration in peroxisomes. DOI: http://dx.doi.org/10.7554/eLife.03640.001 Amino acids are the building blocks of proteins, and the order of the amino acids in a protein is determined by the order in which ‘codons’ appear in a messenger RNA molecule. Most codons represent a specific amino acid, but there are also three stop codons that are used to mark the end of a protein. When the cellular machinery that ‘translates’ the messenger RNA molecule into a protein encounters a stop codon, it stops and releases the completed protein. Sometimes, however, the stop codon is not interpreted as a stop signal, and the translation of the messenger RNA molecule continues until another stop codon is encountered. This process is known as readthrough. Some organisms, in particular viruses and fungi, use readthrough to produce a wider range of proteins than their genomes would otherwise allow. While readthrough also occurs in higher organisms such as mammals, it is not known if the resulting proteins perform extra functions that the original protein does not perform. A number of factors affect whether readthrough occurs when an mRNA template is being translated. For example, each of the three stop codons has a different likelihood of having its stop signal misinterpreted, and the mRNA sequence that surrounds the stop codon can also affect the likelihood of readthrough. Schueren et al. have developed a computational model that estimates how common this form of translational readthrough is in the human genome. The model was based on the identity of the stop codons themselves and the surrounding mRNA sequence. This model was then combined with another model that identifies proteins that are targeted to a structure inside a cell called the peroxisome, which is where a number of essential energy-releasing reactions take place. The combined model enabled Schueren et al. to identify proteins that both perform functions in the peroxisome and are likely to be formed by readthrough. The combined model suggested a protein that is a part of lactate dehydrogenase: an enzyme that speeds up chemical reactions that are important for the cell to produce energy. Low levels of lactate dehydrogenase had previously been found in the peroxisome, despite it apparently lacking a specific sequence of amino acids that proteins need to have to enter the peroxisome. However, Schueren et al. confirmed experimentally that readthrough does occur for the lactate dehydrogenase component identified by the model, revealing that it contains a ‘hidden’ peroxisome-targeting region. Furthermore, when more translational readthrough occurred, more lactate dehydrogenase was found in the peroxisomes. This unusual way that lactate dehydrogenase enters the peroxisome is an example of how the cell optimizes the used of the genetic information encoded in the genome and in messenger RNA. Translational readthrough always ensures that a certain proportion of lactate dehydrogenase will be brought to the peroxisome. The computational model developed here will be a valuable tool to identify other such proteins produced from genomes, including the human genome and those of other species. DOI: http://dx.doi.org/10.7554/eLife.03640.002