Succinylation profiles of brain injury after intracerebral hemorrhage

Protein posttranslational modifications (PTMs) regulate the biological processes of human diseases by genetic code expansion and cellular pathophysiology regulation; however, system-wide changes in PTM levels in the intracerebral hemorrhage (ICH) brain remain poorly understood. Succinylation refers to a major PTM during the regulation of multiple biological processes. In this study, according to the methods of quantitative succinyllysine proteomics based on high-resolution mass spectrometry, we investigated ICH-associated brain protein succinyllysine modifications and obtained 3,680 succinylated sites and quantified around 3,530 sites. Among them, 25 succinyllysine sites on 23 proteins were upregulated (hypersuccinylated), whereas 13 succinyllysine sites on 12 proteins were downregulated (hyposuccinylated) following ICH. The cell component enrichment analysis of these succinylproteins with significant changes showed that 58.3% of the hyposuccinylated proteins were observed in the mitochondria, while the hyper-succinylproteins located in mitochondria decreased in the percentage to about 35% in ICH brains with a concomitant increase in the percentage of cytoplasm to 30.4%. Further bioinformatic analysis showed that the succinylproteins were mostly mitochondria and synapse-related subcellular located and involved in many pathophysiological processes, like metabolism, synapse working, and ferroptosis. Moreover, the integrative analysis of our succinylproteomics data and previously published transcriptome data showed that the mRNAs matched by most differentially succinylated proteins were especially highly expressed in neurons, endothelial cells, and astrocytes. Our study uncovers some succinylation-affected processes and pathways in response to ICH brains and gives us novel insights into understanding pathophysiological processes of brain injury caused by ICH.

E3 ligase Nedd4l promotes antiviral innate immunity by catalyzing K29-linked cysteine ubiquitination of TRAF3

Ubiquitination is one of the most prevalent protein posttranslational modifications. Here, we show that E3 ligase Nedd4l positively regulates antiviral immunity by catalyzing K29-linked cysteine ubiquitination of TRAF3. Deficiency of Nedd4l significantly impairs type I interferon and proinflammatory cytokine production induced by virus infection both in vitro and in vivo. Nedd4l deficiency inhibits virus-induced ubiquitination of TRAF3, the binding between TRAF3 and TBK1, and subsequent phosphorylation of TBK1 and IRF3. Nedd4l directly interacts with TRAF3 and catalyzes K29-linked ubiquitination of Cys56 and Cys124, two cysteines that constitute zinc fingers, resulting in enhanced association between TRAF3 and E3 ligases, cIAP1/2 and HECTD3, and also increased K48/K63-linked ubiquitination of TRAF3. Mutation of Cys56 and Cys124 diminishes Nedd4l-catalyzed K29-linked ubiquitination, but enhances association between TRAF3 and the E3 ligases, supporting Nedd4l promotes type I interferon production in response to virus by catalyzing ubiquitination of the cysteines in TRAF3.

My personal mutanome: a computational genomic medicine platform for searching network perturbing alleles linking genotype to phenotype

Massive genome sequencing data have inspired new challenges in personalized treatments and facilitated oncological drug discovery. We present a comprehensive database, My Personal Mutanome (MPM), for accelerating the development of precision cancer medicine protocols. MPM contains 490,245 mutations from over 10,800 tumor exomes across 33 cancer types in The Cancer Genome Atlas mapped to 94,563 structure-resolved/predicted protein-protein interaction interfaces (“edgetic”) and 311,022 functional sites (“nodetic”), including ligand-protein binding sites and 8 types of protein posttranslational modifications. In total, 8884 survival results and 1,271,132 drug responses are obtained for these mapped interactions. MPM is available at https://mutanome.lerner.ccf.org.

Capsule network for protein ubiquitination site prediction

Ubiquitination modification is one of the most important protein posttranslational modifications used in many biological processes. Traditional ubiquitination site determination methods are expensive and time-consuming, whereas calculation-based prediction methods can accurately and efficiently predict ubiquitination sites. This study used a convolutional neural network and a capsule network in deep learning to design a deep learning model, “Caps-Ubi,” for multispecies ubiquitination site prediction. Two encoding methods, one-of-K and the amino acid continuous type were used to characterize the sequence pattern of ubiquitination sites. The proposed Caps-Ubi predictor achieved an accuracy of 0.91, a sensitivity of 0.93, a specificity of 0.89, a measure-correlate-prediction of 0.83, and an area under receiver operating characteristic curve value of 0.96, which outperformed the other tested predictors.

Different phosphorylation and farnesylation patterns tune Rnd3–14-3-3 interaction in distinct mechanisms

Different protein posttranslational modifications (PTMs) patterns affect the binding thermodynamics and kinetics and their molecular mechanism of multivalent protein–protein interaction (PPIs).