Long-Lasting Growth Hormone Regulated by the Ubiquitin-Proteasome System

To increase the half-life of growth hormones, we proposed its long-lasting regulation through the ubiquitin-proteasome system (UPS). We identified lysine residues (K67, K141, and K166) that are involved in the ubiquitination of human growth hormone (hGH) using ubiquitination site prediction programs to validate the ubiquitination sites, and then substituted these lysine residues with arginine residues. We identified the most effective substituent (K141R) to prevent ubiquitination and named it AUT-hGH. hGH was expressed and purified in the form of hGH-His, and ubiquitination was first verified at sites containing K141 in the blood stream. Through the study, we propose that AUT-hGH with an increased half-life could be used as a long-lasting hGH in the blood stream.

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.

Ubiquitination of RIPK1 regulates its activation mediated by TNFR1 and TLRs signaling in distinct manners

RIPK1 is a death-domain (DD) containing kinase involved in regulating apoptosis, necroptosis and inflammation. RIPK1 activation is known to be regulated by its DD-mediated interaction and ubiquitination, though underlying mechanisms remain incompletely understood. Here we show that K627 in human RIPK1-DD and its equivalent K612 in murine RIPK1-DD is a key ubiquitination site that regulates the overall ubiquitination pattern of RIPK1 and its DD-mediated interactions with other DD-containing proteins. K627R/K612R mutation inhibits the activation of RIPK1 and blocks both apoptosis and necroptosis mediated by TNFR1 signaling. However, Ripk1K612R/K612R mutation sensitizes cells to necroptosis and caspase-1 activation in response to TLRs signaling. Ripk1K612R/K612R mice are viable, but develop age-dependent reduction of RIPK1 expression, spontaneous intestinal inflammation and splenomegaly, which can be rescued by antibiotic treatment and partially by Ripk3 deficiency. Furthermore, we show that the interaction of RIPK1 with FADD contributes to suppressing the activation of RIPK3 mediated by TLRs signaling. Our study demonstrates the distinct roles of K612 ubiquitination in mRIPK1/K627 ubiquitination in hRIPK1 in regulating its pro-death kinase activity in response to TNFα and pro-survival activity in response to TLRs signaling.

Impaired RIPK1 ubiquitination sensitizes mice to TNF toxicity and inflammatory cell death

Receptor-interacting protein 1 (RIP1; RIPK1) is a key regulator of multiple signaling pathways that mediate inflammatory responses and cell death. TNF-TNFR1 triggered signaling complex formation, subsequent NF-κB and MAPK activation and induction of cell death involve RIPK1 ubiquitination at several lysine residues including Lys376 and Lys115. Here we show that mutating the ubiquitination site K376 of RIPK1 (K376R) in mice activates cell death resulting in embryonic lethality. In contrast to Ripk1K376R/K376R mice, Ripk1K115R/K115R mice reached adulthood and showed slightly higher responsiveness to TNF-induced death. Cell death observed in Ripk1K376R/K376R embryos relied on RIPK1 kinase activity as administration of RIPK1 inhibitor GNE684 to pregnant heterozygous mice effectively blocked cell death and prolonged survival. Embryonic lethality of Ripk1K376R/K376R mice was prevented by the loss of TNFR1, or by simultaneous deletion of caspase-8 and RIPK3. Interestingly, elimination of the wild-type allele from adult Ripk1K376R/cko mice was tolerated. However, adult Ripk1K376R/cko mice were exquisitely sensitive to TNF-induced hypothermia and associated lethality. Absence of the K376 ubiquitination site diminished K11-linked, K63-linked, and linear ubiquitination of RIPK1, and promoted the assembly of death-inducing cellular complexes, suggesting that multiple ubiquitin linkages contribute to the stability of the RIPK1 signaling complex that stimulates NF-κB and MAPK activation. In contrast, mutating K115 did not affect RIPK1 ubiquitination or TNF stimulated NF-κB and MAPK signaling. Overall, our data indicate that selective impairment of RIPK1 ubiquitination can lower the threshold for RIPK1 activation by TNF resulting in cell death and embryonic lethality.

Deep ubiquitination site profiling by single-shot data-independent acquisition mass spectrometry

We report a highly optimized proteomics method for in-depth ubiquitination profiling, which combines efficient protein extraction and data-independent acquisition mass spectrometry (DIA-MS). Employing DIA for both spectral library generation and single-shot sample analysis, we quantify up to 70,000 ubiquitinated peptides per MS run with high precision, data completeness and throughput. Our approach resolves the dynamics of ubiquitination and protein degradation with an unprecedented analytical depth.

Allosteric activation of MALT1 by its ubiquitin-binding Ig3 domain

The catalytic activity of the protease MALT1 is required for adaptive immune responses and regulatory T (Treg)-cell development, while dysregulated MALT1 activity can lead to lymphoma. MALT1 activation requires its monoubiquitination on lysine 644 (K644) within the Ig3 domain, localized adjacent to the protease domain. The molecular requirements for MALT1 monoubiquitination and the mechanism by which monoubiquitination activates MALT1 had remained elusive. Here, we show that the Ig3 domain interacts directly with ubiquitin and that an intact Ig3-ubiquitin interaction surface is required for the conjugation of ubiquitin to K644. Moreover, by generating constitutively active MALT1 mutants that overcome the need for monoubiquitination, we reveal an allosteric communication between the ubiquitination site K644, the Ig3-protease interaction surface, and the active site of the protease domain. Finally, we show that MALT1 mutants that alter the Ig3-ubiquitin interface impact the biological response of T cells. Thus, ubiquitin binding by the Ig3 domain promotes MALT1 activation by an allosteric mechanism that is essential for its biological function.

Computational Prediction of Ubiquitination Proteins Using Evolutionary Profiles and Functional Domain Annotation

Background: Ubiquitination, as a post-translational modification, is a crucial biological process in cell signaling, apoptosis, and localization. Identification of ubiquitination proteins is of fundamental importance for understanding the molecular mechanisms in biological systems and diseases. Although high-throughput experimental studies using mass spectrometry have identified many ubiquitination proteins and ubiquitination sites, the vast majority of ubiquitination proteins remain undiscovered, even in well-studied model organisms. Objective: To reduce experimental costs, computational methods have been introduced to predict ubiquitination sites, but the accuracy is unsatisfactory. If it can be predicted whether a protein can be ubiquitinated or not, it will help in predicting ubiquitination sites. However, all the computational methods so far can only predict ubiquitination sites. Methods: In this study, the first computational method for predicting ubiquitination proteins without relying on ubiquitination site prediction has been developed. The method extracts features from sequence conservation information through a grey system model, as well as functional domain annotation and subcellular localization. Results: Together with the feature analysis and application of the relief feature selection algorithm, the results of 5-fold cross-validation on three datasets achieved a high accuracy of 90.13%, with Matthew’s correlation coefficient of 80.34%. The predicted results on an independent test data achieved 87.71% as accuracy and 75.43% of Matthew’s correlation coefficient, better than the prediction from the best ubiquitination site prediction tool available. Conclusion: Our study may guide experimental design and provide useful insights for studying the mechanisms and modulation of ubiquitination pathways. The code is available at: https://github.com/Chunhuixu/UBIPredic_QWRCHX.

Structure of the Fanconi Anemia Core–UBE2T complex poised to ubiquitinate bound FANCI–FANCD2

ABSTRACTThe Fanconi Anemia (FA) pathway is essential for the repair of DNA interstrand crosslinks (ICLs). The pathway is activated when a replication fork stalls because of an ICL or other replication stress. A central event in pathway activation is the mono-ubiquitination of the FANCI-FANCD2 (ID) complex by the FA Core complex, a ubiquitin ligase of nine subunits. Here we describe the cryo-EM structures of the 1.1 MDa FA Core at 3.1 angstroms, except for the FANCA subunit at 3.4, and of the complex containing Core, ID and the UBE2T ubiquitin conjugating enzyme at 4.2 angstroms. The Core has unusual stoichiometry with two copies of FANCB, FAAP100, FANCA, FAAP20, FANCG, FANCL, but only a single copy of FANCC, FANCE and FANCF. This is due to homodimers of FANCA and FANCB having incompatible 2-fold symmetry, resulting in an overall asymmetric assembly of the other subunits. The asymmetry is crucial, as it prevents the binding of a second FANC-C-E-F sub-complex that inhibits UBE2T recruitment by FANCL, and instead creates an ID binding site. The single active FANCL-UBE2T binds next to the FANCD2 ubiquitination site, prying open the FANCI-FANCD2 interface within which the ubiquitination sites are buried. These structures and biochemical data indicate a single active site ubiquitinates FANCD2 and FANCI sequentially, shedding light on a central event in the FA pathway.

Prediction of Protein Ubiquitination Sites in Arabidopsis thaliana

Background: As one of the most important reversible protein post-translation modification types, ubiquitination plays a significant role in the regulation of many biological processes, such as cell division, signal transduction, apoptosis and immune response. Protein ubiquitination usually occurs when ubiquitin molecule is attached to a lysine on a target protein, which is also known as “lysine ubiquitination”. Objective: In order to investigate the molecular mechanisms of ubiquitination-related biological processes, the crucial first step is the identification of ubiquitination sites. However, conventional experimental methods in detecting ubiquitination sites are often time-consuming and a large number of ubiquitination sites remain unidentified. In this study, a ubiquitination site prediction method for Arabidopsis thaliana was developed using a Support Vector Machine (SVM). Methods: We collected 3009 experimentally validated ubiquitination sites on 1607 proteins in A. thaliana to construct the training set. Three feature encoding schemes were used to characterize the sequence patterns around ubiquitination sites, including AAC, Binary and CKSAAP. The maximum Relevance and Minimum Redundancy (mRMR) feature selection method was employed to reduce the dimensionality of input features. Five-fold cross-validation and independent tests were used to evaluate the performance of the established models. Results: As a result, the combination of AAC and CKSAAP encoding schemes yielded the best performance with the accuracy and AUC of 81.35% and 0.868 in the independent test. We also generated an online predictor termed as AraUbiSite, which is freely accessible at: http://systbio.cau.edu.cn/araubisite. Conclusion: We developed a well-performed prediction tool for large-scale ubiquitination site identification in A. thaliana. It is hoped that the current work will speed up the process of identification of ubiquitination sites in A. thaliana and help to further elucidate the molecular mechanisms of ubiquitination in plants.