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理解致病微管蛋白突变的分子机制和预测表型效应。

Understanding molecular mechanisms and predicting phenotypic effects of pathogenic tubulin mutations.

机构信息

Wellcome Trust Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom.

MRC Human Genetics Unit, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, United Kingdom.

出版信息

PLoS Comput Biol. 2022 Oct 7;18(10):e1010611. doi: 10.1371/journal.pcbi.1010611. eCollection 2022 Oct.

DOI:10.1371/journal.pcbi.1010611
PMID:36206299
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9581425/
Abstract

Cells rely heavily on microtubules for several processes, including cell division and molecular trafficking. Mutations in the different tubulin-α and -β proteins that comprise microtubules have been associated with various diseases and are often dominant, sporadic and congenital. While the earliest reported tubulin mutations affect neurodevelopment, mutations are also associated with other disorders such as bleeding disorders and infertility. We performed a systematic survey of tubulin mutations across all isotypes in order to improve our understanding of how they cause disease, and increase our ability to predict their phenotypic effects. Both protein structural analyses and computational variant effect predictors were very limited in their utility for differentiating between pathogenic and benign mutations. This was even worse for those genes associated with non-neurodevelopmental disorders. We selected tubulin-α and -β disease mutations that were most poorly predicted for experimental characterisation. These mutants co-localise to the mitotic spindle in HeLa cells, suggesting they may exert dominant-negative effects by altering microtubule properties. Our results show that tubulin mutations represent a blind spot for current computational approaches, being much more poorly predicted than mutations in most human disease genes. We suggest that this is likely due to their strong association with dominant-negative and gain-of-function mechanisms.

摘要

细胞依赖微管进行多种过程,包括细胞分裂和分子运输。组成微管的不同微管蛋白-α和-β蛋白的突变与各种疾病有关,并且通常是显性的、散发性的和先天性的。虽然最早报道的微管突变影响神经发育,但突变也与其他疾病有关,如出血性疾病和不孕。我们对所有同种型的微管蛋白突变进行了系统调查,以提高我们对它们如何引起疾病的理解,并提高我们预测其表型效应的能力。蛋白质结构分析和计算变异效应预测器在区分致病性和良性突变方面的作用都非常有限。对于与非神经发育障碍相关的基因来说,情况更糟。我们选择了最难以预测实验特征的微管蛋白-α和-β疾病突变。这些突变体在 HeLa 细胞中与有丝分裂纺锤体共定位,表明它们可能通过改变微管特性发挥显性负效应。我们的结果表明,微管突变是当前计算方法的一个盲点,其预测能力比大多数人类疾病基因的突变差得多。我们认为这可能是由于它们与显性负和功能获得机制的强烈关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4312/9581425/0dacb69007d0/pcbi.1010611.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4312/9581425/52d878127046/pcbi.1010611.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4312/9581425/0dacb69007d0/pcbi.1010611.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4312/9581425/52d878127046/pcbi.1010611.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4312/9581425/0dacb69007d0/pcbi.1010611.g002.jpg

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本文引用的文献

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Nat Commun. 2022 Jul 6;13(1):3895. doi: 10.1038/s41467-022-31686-6.
2
Interpreting protein variant effects with computational predictors and deep mutational scanning.用计算预测器和深度突变扫描来解释蛋白质变异的影响。
Dis Model Mech. 2022 Jun 1;15(6). doi: 10.1242/dmm.049510. Epub 2022 Jun 23.
3
Diverse Molecular Mechanisms Underlying Pathogenic Protein Mutations: Beyond the Loss-of-Function Paradigm.
纤毛病患者的变异揭示了TUBB4B在轴丝微管中的细胞器特异性功能。
Science. 2024 Apr 26;384(6694):eadf5489. doi: 10.1126/science.adf5489.
4
Editorial: Tubulinopathies: fundamental and clinical challenges.社论:微管蛋白病:基础与临床挑战
Front Cell Neurosci. 2023 Oct 13;17:1296958. doi: 10.3389/fncel.2023.1296958. eCollection 2023.
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Dynamics of TUBB protein with five majorly occurring natural variants: a risk of cortical dysplasia.具有五种主要自然变体的TUBB蛋白的动力学:皮质发育异常的风险
J Mol Model. 2023 Mar 16;29(4):100. doi: 10.1007/s00894-023-05506-7.
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