Ubiquitin-mediated processes orchestrate critical DNA-damage signaling and repair pathways. We identify human DVC1 (C1orf124; Spartan) as a cell cycle-regulated anaphase-promoting complex (APC) substrate that accumulates at stalled replication forks. DVC1 recruitment to sites of replication stress requires its ubiquitin-binding UBZ domain and PCNA-binding PIP box motif but is independent of RAD18-mediated PCNA monoubiquitylation. Via a conserved SHP box, DVC1 recruits the ubiquitin-selective chaperone p97 to blocked replication forks, which may facilitate p97-dependent removal of translesion synthesis (TLS) DNA polymerase η (Pol η) from monoubiquitylated PCNA. DVC1 knockdown enhances UV light-induced mutagenesis, and depletion of human DVC1 or the Caenorhabditis elegans ortholog DVC-1 causes hypersensitivity to replication stress-inducing agents. Our findings establish DVC1 as a DNA damage-targeting p97 adaptor that protects cells from deleterious consequences of replication blocks and suggest an important role of p97 in ubiquitin-dependent regulation of TLS.

SummaryThe linear ubiquitin (Ub) chain assembly complex (LUBAC) generates Met1-linked “linear” Ub chains that regulate the activation of the nuclear factor κB (NFκB) transcription factor and other processes. We recently discovered OTULIN as a deubiquitinase that specifically cleaves Met1-linked polyUb. Now, we show that OTULIN binds via a conserved PUB-interacting motif (PIM) to the PUB domain of the LUBAC component HOIP. Crystal structures and nuclear magnetic resonance experiments reveal the molecular basis for the high-affinity interaction and explain why OTULIN binds the HOIP PUB domain specifically. Analysis of LUBAC-induced NFκB signaling suggests that OTULIN needs to be present on LUBAC in order to restrict Met1-polyUb signaling. Moreover, LUBAC-OTULIN complex formation is regulated by OTULIN phosphorylation in the PIM. Phosphorylation of OTULIN prevents HOIP binding, whereas unphosphorylated OTULIN is part of the endogenous LUBAC complex. Our work exemplifies how coordination of ubiquitin assembly and disassembly activities in protein complexes regulates individual Ub linkage types.

Accurate methods to assess the pathogenicity of mutations are needed to fully leverage the possibilities of genome sequencing in diagnosis. Current data-driven and bioinformatics approaches are, however, limited by the large number of new variations found in each newly sequenced genome, and often do not provide direct mechanistic insight. Here we demonstrate, for the first time, that saturation mutagenesis, biophysical modeling and co-variation analysis, performed in silico, can predict the abundance, metabolic stability, and function of proteins inside living cells. As a model system, we selected the human mismatch repair protein, MSH2, where missense variants are known to cause the hereditary cancer predisposition disease, known as Lynch syndrome. We show that the majority of disease-causing MSH2 mutations give rise to folding defects and proteasome-dependent degradation rather than inherent loss of function, and accordingly our in silico modeling data accurately identifies disease-causing mutations and outperforms the traditionally used genetic disease predictors. Thus, in conclusion, in silico biophysical modeling should be considered for making genotype-phenotype predictions and for diagnosis of Lynch syndrome, and perhaps other hereditary diseases.

Understanding and predicting how amino acid substitutions affect proteins is key to our basic understanding of protein function and evolution. Amino acid changes may affect protein function in a number of ways including direct perturbations of activity or indirect effects on protein folding and stability. We have analysed 6749 experimentally determined variant effects from multiplexed assays on abundance and activity in two proteins (NUDT15 and PTEN) to quantify these effects, and find that a third of the variants cause loss of function, and about half of loss-of-function variants also have low cellular abundance. We analyse the structural and mechanistic origins of loss of function, and use the experimental data to find residues important for enzymatic activity. We performed computational analyses of protein stability and evolutionary conservation and show how we may predict positions where variants cause loss of activity or abundance. In this way, our results link thermodynamic stability and evolutionary conservation to experimental studies of different properties of protein fitness landscapes.