Aggarwal Suruchi, Banerjee Sanjay K, Talukdar Narayan Chandra, Yadav Amit Kumar
Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, India.
Division of Life Sciences, Institute of Advanced Study in Science and Technology, Guwahati, India.
Front Genet. 2020 Apr 30;11:356. doi: 10.3389/fgene.2020.00356. eCollection 2020.
Sirtuins are protein deacetylases that play a protective role in cardiovascular diseases (CVDs), as well as many other diseases. Absence of sirtuins can lead to hyperacetylation of both nuclear and mitochondrial proteins leading to metabolic dysregulation. The protein post-translational modifications (PTMs) are known to crosstalk among each other to bring about complex phenotypic outcomes. Various PTM types such as acetylation, ubiquitination, and phosphorylation, and so on, drive transcriptional regulation and metabolism, but such crosstalks are poorly understood. We integrated protein-protein interactions (PPI) and PTMs from several databases to integrate information on 1,251 sirtuin-interacting proteins, of which 544 are associated with cardiac diseases. Based on the ∼100,000 PTM sites obtained for sirtuin interactors, we observed that the frequency of PTM sites (83 per protein), as well as PTM types (five per protein), is higher than the global average for human proteome. We found that ∼60-70% PTM sites fall into ordered regions. Approximately 83% of the sirtuin interactors contained at least one competitive crosstalk () site, with half of the sites occurring in CVD-associated proteins. A large proportion of identified crosstalk sites were observed for acetylation and ubiquitination competition. We identified 614 proteins containing PTM hotspots (≥5 PTM sites) and 133 proteins containing crosstalk hotspots (≥3 crosstalk sites). We observed that a large proportion of disease-associated sequence variants were found in PTM motifs of CVD proteins. We identified seven proteins (TP53, LMNA, MAPT, ATP2A2, NCL, APEX1, and HIST1H3A) containing disease-associated variants in PTM and crosstalk hotspots. This is the first comprehensive bioinformatics analysis on sirtuin interactors with respect to PTMs and their crosstalks. This study forms a platform for generating interesting hypotheses that can be tested for a deeper mechanistic understanding gained or derived from big-data analytics.
沉默调节蛋白是蛋白质去乙酰化酶，在心血管疾病（CVD）以及许多其他疾病中发挥保护作用。沉默调节蛋白的缺失会导致核蛋白和线粒体蛋白的过度乙酰化，从而导致代谢失调。已知蛋白质翻译后修饰（PTM）之间会相互作用，从而产生复杂的表型结果。各种PTM类型，如乙酰化、泛素化和磷酸化等，驱动转录调控和代谢，但这种相互作用还知之甚少。我们整合了来自多个数据库的蛋白质-蛋白质相互作用（PPI）和PTM，以整合关于1251个与沉默调节蛋白相互作用的蛋白质的信息，其中544个与心脏疾病相关。基于为沉默调节蛋白相互作用分子获得的约100,000个PTM位点，我们观察到PTM位点的频率（每个蛋白质83个）以及PTM类型（每个蛋白质5种）高于人类蛋白质组的全球平均水平。我们发现约60-70%的PTM位点位于有序区域。大约83%的沉默调节蛋白相互作用分子包含至少一个竞争性相互作用（）位点，其中一半的位点出现在与CVD相关的蛋白质中。在乙酰化和泛素化竞争中观察到很大比例的已鉴定相互作用位点。我们鉴定出614个含有PTM热点（≥5个PTM位点）的蛋白质和133个含有相互作用热点（≥3个相互作用位点）的蛋白质。我们观察到在CVD蛋白质的PTM基序中发现了很大比例的疾病相关序列变异。我们鉴定出7种蛋白质（TP53、LMNA、MAPT、ATP2A2、NCL、APEX1和HIST1H3A）在PTM和相互作用热点中含有疾病相关变异。这是首次关于沉默调节蛋白相互作用分子在PTM及其相互作用方面的全面生物信息学分析。这项研究形成了一个平台，用于产生有趣的假设，这些假设可用于进行测试，以从大数据分析中获得或推导更深入的机制理解。
