Understanding molecular mechanisms and predicting phenotypic effects of pathogenic tubulin mutations
Understanding molecular mechanisms and predicting phenotypic effects of pathogenic tubulin mutations
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DOI：
10.1101/2022.06.16.496400
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发表时间：
2022-06
影响因子：
4.3
通讯作者：
T. Attard;J. Welburn;J. Marsh
中科院分区：
文献类型：
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作者：
T. Attard;J. Welburn;J. Marsh
细胞严重依赖微管进行几个过程，包括细胞分裂和分子运输。构成微管的不同微管蛋白-α和-β蛋白的突变与各种疾病相关，并且通常是显性的、散发的和先天性的。虽然最早报道的微管蛋白突变影响神经发育，但突变也与其他疾病如出血性疾病和不孕症有关。我们对所有同种型的微管蛋白突变进行了系统的调查，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因子在区分致病性和良性突变方面的效用非常有限。对于那些与非神经发育障碍相关的基因来说，情况更糟。我们选择了在实验表征中预测最差的微管蛋白-α和-β疾病突变。这些突变体共定位于HeLa细胞中的有丝分裂纺锤体，这表明它们可能通过改变微管特性来发挥显性负效应。我们的研究结果表明，微管蛋白突变代表了目前计算方法的盲点，比大多数人类疾病基因的突变预测更差。我们认为这可能是由于它们与显性负性和功能获得机制密切相关。
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.