Non-classical protein secretion in bacteria.
Non-classical protein secretion in bacteria.
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DOI：
10.1186/1471-2180-5-58
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发表时间：
2005-10-07
期刊：
影响因子：
4.2
通讯作者：
Brunak S
中科院分区：
文献类型：
--
作者：
Bendtsen JD;Kiemer L;Fausbøll A;Brunak S
我们介绍了细菌非经典分泌物的概述，并提出了一种预测方法，用于识别信号肽非依赖性分泌途径中的蛋白质。我们已经编制了一份蛋白质清单，尽管没有信号肽，但仍在细胞外发现。其中一些蛋白质在细胞质中也有已知的作用，这意味着它们可能是所谓的具有多种功能的“月光闪电”蛋白质。进行了全面的文献检索，以汇编目前已知的细菌非经典分泌蛋白的列表。对这些序列应用模式寻找方法，以确定负责其分泌的假定信号序列或基序。在汇编的非经典分泌蛋白质列表中，我们没有发现任何大多数蛋白质的信号或基序特征，并得出结论，这些蛋白质确实似乎以一种新的方式分泌。然而，我们也表明，表面上非经典分泌的蛋白质仍然在氨基酸组成、二级结构和无序区域等性质上区别于细胞蛋白质。具体地说，对无序性的预测表明，细菌分泌蛋白比它们的细胞质分泌蛋白在结构上更无序。最后，使用人工神经网络构建了基于蛋白质特征的方法来识别革兰氏阳性和革兰氏阴性细菌中非经典分泌的蛋白质。我们提出了一种公开可用的预测方法，能够区分这组蛋白质和其他蛋白质，从而能够识别新的非经典分泌蛋白质。我们推荐大肠杆菌和枯草芽孢杆菌中非经典分泌蛋白的候选者。该预测方法可在网上获得。
We present an overview of bacterial non-classical secretion and a prediction method for identification of proteins following signal peptide independent secretion pathways. We have compiled a list of proteins found extracellularly despite the absence of a signal peptide. Some of these proteins also have known roles in the cytoplasm, which means they could be so-called "moon-lightning" proteins having more than one function. A thorough literature search was conducted to compile a list of currently known bacterial non-classically secreted proteins. Pattern finding methods were applied to the sequences in order to identify putative signal sequences or motifs responsible for their secretion. We have found no signal or motif characteristic to any majority of the proteins in the compiled list of non-classically secreted proteins, and conclude that these proteins, indeed, seem to be secreted in a novel fashion. However, we also show that the apparently non-classically secreted proteins are still distinguished from cellular proteins by properties such as amino acid composition, secondary structure and disordered regions. Specifically, prediction of disorder reveals that bacterial secretory proteins are more structurally disordered than their cytoplasmic counterparts. Finally, artificial neural networks were used to construct protein feature based methods for identification of non-classically secreted proteins in both Gram-positive and Gram-negative bacteria. We present a publicly available prediction method capable of discriminating between this group of proteins and other proteins, thus allowing for the identification of novel non-classically secreted proteins. We suggest candidates for non-classically secreted proteins in Escherichia coli and Bacillus subtilis. The prediction method is available online.
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影响因子：
14.9
作者：
Bairoch, A;Apweiler, R
通讯作者：
Apweiler, R
影响因子：
3.2
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通讯作者：
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