intrinsic disordered regions

  • 文章类型: Journal Article
    感知和响应渗透波动的能力对于维持细胞完整性至关重要。我们使用基因共质分析来确定TSC22D2,WNK1和NRBP1在调节细胞体积稳态方面的未被理解的关系。所有这些基因都具有旁系同源物,并且在功能上被缓冲以进行渗透感应和细胞体积控制。在高渗应激的几秒钟内,TSC22D,WNK,和NRBP家族成员物理缔合成生物分子缩合物,一个依赖于内在无序区域(IDR)的过程。对后生动物的这些蛋白质家族的仔细检查表明,TSC22D基因与NRBPs中的一个结构域一起进化,该结构域与TSC22D蛋白特异性结合,我们称之为NbrT(NRBP与TSC22D结合区),这种共同进化伴随着WNK家族激酶中IDR长度的快速扩展。我们的研究表明,TSC22D,WNK,和NRBP基因在后生动物中进化,以共同调节响应渗透压的快速细胞体积变化。
    The ability to sense and respond to osmotic fluctuations is critical for the maintenance of cellular integrity. We used gene co-essentiality analysis to identify an unappreciated relationship between TSC22D2, WNK1, and NRBP1 in regulating cell volume homeostasis. All of these genes have paralogs and are functionally buffered for osmo-sensing and cell volume control. Within seconds of hyperosmotic stress, TSC22D, WNK, and NRBP family members physically associate into biomolecular condensates, a process that is dependent on intrinsically disordered regions (IDRs). A close examination of these protein families across metazoans revealed that TSC22D genes evolved alongside a domain in NRBPs that specifically binds to TSC22D proteins, which we have termed NbrT (NRBP binding region with TSC22D), and this co-evolution is accompanied by rapid IDR length expansion in WNK-family kinases. Our study reveals that TSC22D, WNK, and NRBP genes evolved in metazoans to co-regulate rapid cell volume changes in response to osmolarity.
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  • 文章类型: Journal Article
    引起神经退行性疾病的蛋白质,如α-突触核蛋白,tau,已知亨廷顿蛋白通过外泌体穿过细胞,细胞外囊泡和隧道纳米管(TNTs)。在细胞间通讯中,外来体和TNTs之间似乎有很好的协同作用。有趣的是,许多已知的主要神经变性蛋白/蛋白水解产物是无前导序列的,并且也据报道通过非常规的蛋白分泌被分泌出细胞。此类包含内在无序的蛋白质和区域(IDR)。这些蛋白质的动态行为是由于它们的异源性构象,这是由于细胞内发生的各种因素而表现出来的。氨基酸序列以及化学修饰对细胞内IDR的功能作用有影响。形成聚集体导致神经变性的蛋白质抵抗自噬和蛋白酶体系统的降解,从而导致隧道纳米管,TNT形成。穿过TNT的蛋白质可能依赖于或不依赖于自噬机制。目前尚不清楚蛋白质的构象是否在其从一个细胞到另一个细胞的运输中起关键作用而不被降解。虽然有一些实验数据,有许多灰色地带需要重新审视。这篇综述提供了对这些分泌到细胞外的无前导蛋白的结构和功能方面的不同观点。在这次审查中,注意力集中在导致无前导分泌蛋白聚集的特征上(从结构功能方面),特别强调了TNT。
    Neurodegenerative disease-causing proteins such as alpha-synuclein, tau, and huntingtin are known to traverse across cells via exosomes, extracellular vesicles and tunneling nanotubes (TNTs). There seems to be good synergy between exosomes and TNTs in intercellular communication. Interestingly, many of the known major neurodegenerative proteins/proteolytic products are leaderless and are also reported to be secreted out of the cell via unconventional protein secretion. Such classes contain intrinsically disordered proteins and regions (IDRs) within them. The dynamic behavior of these proteins is due to their heterogenic conformations that is exhibited owing to various factors that occur inside the cells. The amino acid sequence along with the chemical modifications has implications on the functional roles of IDRs inside the cells. Proteins that form aggregates resulting in neurodegeneration become resistant to degradation by the processes of autophagy and proteasome system thus leading to Tunneling nanotubes, TNT formation. The proteins that traverse across TNTs may or may not be dependent on the autophagy machinery. It is not yet clear whether the conformation of the protein plays a crucial role in its transport from one cell to another without getting degraded. Although there is some experimental data, there are many grey areas which need to be revisited. This review provides a different perspective on the structural and functional aspects of these leaderless proteins that get secreted outside the cell. In this review, attention has been focused on the characteristic features that lead to aggregation of leaderless secretory proteins (from structural-functional aspect) with special emphasis on TNTs.
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  • 文章类型: Case Reports
    Two adult siblings born to first-cousin parents presented a clinical phenotype reminiscent of Rothmund-Thomson syndrome (RTS), implying fragile hair, absent eyelashes/eyebrows, bilateral cataracts, mottled pigmentation, dental decay, hypogonadism, and osteoporosis. As the clinical suspicion was not supported by the sequencing of RECQL4, the RTS2-causative gene, whole exome sequencing was applied and disclosed the homozygous variants c.83G>A (p.Gly28Asp) and c.2624A>C (p.Glu875Ala) in the nucleoporin 98 (NUP98) gene. Though both variants affect highly conserved amino acids, the c.83G>A looked more intriguing due to its higher pathogenicity score and location of the replaced amino acid between phenylalanine-glycine (FG) repeats within the first NUP98 intrinsically disordered region. Molecular modeling studies of the mutated NUP98 FG domain evidenced a dispersion of the intramolecular cohesion elements and a more elongated conformational state compared to the wild type. This different dynamic behavior may affect the NUP98 functions as the minor plasticity of the mutated FG domain undermines its role as a multi-docking station for RNA and proteins, and the impaired folding can lead to the weakening or the loss of specific interactions. The clinical overlap of NUP98-mutated and RTS2/RTS1 patients, accounted by converging dysregulated gene networks, supports this first-described constitutional NUP98 disorder, expanding the well-known role of NUP98 in cancer.
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  • 文章类型: Journal Article
    固有无序区域(IDR)执行许多细胞功能,并且在蛋白质序列中的长度和位置各不相同。这种多样性导致了潜在的成分偏差的变化,这些都是在短暂的vs.长IDR。我们分析了四类疾病的组成偏差:完全无序的蛋白质;短IDR;长IDR;和结合IDR。我们确定了三个不同的偏见:对于完全无序的蛋白质,短IDR和长IDR和绑定IDR的组合。我们还研究了由主要疾病预测因子产生的推定疾病的组成偏倚,发现它与天然疾病的偏倚相似。有趣的是,不同方法的疾病预测的准确性与预测的成分偏差的正确性相关,突出了成分偏差的重要性。对于具有成分偏差的无序类,其预测质量相对较低,这与“通用”无序偏差最不同,而对于具有最相似偏见的班级来说要高得多。我们发现,不同的预测因子在不同类别的疾病中表现最佳。这表明,没有一个单一的预测指标是普遍最好的,并激发了结合针对特定障碍类别的模型的新体系结构的开发。
    Intrinsically disordered regions (IDRs) carry out many cellular functions and vary in length and placement in protein sequences. This diversity leads to variations in the underlying compositional biases, which were demonstrated for the short vs. long IDRs. We analyze compositional biases across four classes of disorder: fully disordered proteins; short IDRs; long IDRs; and binding IDRs. We identify three distinct biases: for the fully disordered proteins, the short IDRs and the long and binding IDRs combined. We also investigate compositional bias for putative disorder produced by leading disorder predictors and find that it is similar to the bias of the native disorder. Interestingly, the accuracy of disorder predictions across different methods is correlated with the correctness of the compositional bias of their predictions highlighting the importance of the compositional bias. The predictive quality is relatively low for the disorder classes with compositional bias that is the most different from the \"generic\" disorder bias, while being much higher for the classes with the most similar bias. We discover that different predictors perform best across different classes of disorder. This suggests that no single predictor is universally best and motivates the development of new architectures that combine models that target specific disorder classes.
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