Stabilisation of stalled replication forks prevents excessive fork reversal and their pathological degradation, which can undermine genome integrity. Here we investigate a physiological role of RAD52 at stalled replication forks by using human cell models depleted of RAD52, a specific small-molecule inhibitor of the RAD52-ssDNA interaction, in vitro and single-molecule analyses. We demonstrate that RAD52 prevents excessive degradation of reversed replication forks by MRE11. Mechanistically, RAD52 binds to the stalled replication fork, promotes its occlusion and counteracts loading of SMARCAL1 in vitro and in vivo. Loss of the RAD52 function results in a slightly-defective replication restart, persistence of under-replicated regions and chromosome instability. Moreover, the RAD52-inhibited cells rely on RAD51 for completion of replication and viability upon replication arrest. Collectively, our data suggest an unexpected gatekeeper mechanism by which RAD52 limits excessive remodelling of stalled replication forks, thus indirectly assisting RAD51 and BRCA2 in protecting forks from unscheduled degradation and preventing genome instability.

The MUS81 complex is crucial for preserving genome stability through the resolution of branched DNA intermediates in mitosis. However, untimely activation of the MUS81 complex in S-phase is dangerous. Little is known about the regulation of the human MUS81 complex and how deregulated activation affects chromosome integrity. Here, we show that the CK2 kinase phosphorylates MUS81 at Serine 87 in late-G2/mitosis, and upon mild replication stress. Phosphorylated MUS81 interacts with SLX4, and this association promotes the function of the MUS81 complex. In line with a role in mitosis, phosphorylation at Serine 87 is suppressed in S-phase and is mainly detected in the MUS81 molecules associated with EME1. Loss of CK2-dependent MUS81 phosphorylation contributes modestly to chromosome integrity, however, expression of the phosphomimic form induces DSBs accumulation in S-phase, because of unscheduled targeting of HJ-like DNA intermediates, and generates a wide chromosome instability phenotype. Collectively, our findings describe a novel regulatory mechanism controlling the MUS81 complex function in human cells. Furthermore, they indicate that, genome stability depends mainly on the ability of cells to counteract targeting of branched intermediates by the MUS81/EME1 complex in S-phase, rather than on a correct MUS81 function in mitosis.

The Schimke immuno-osseous dysplasia is an autosomal recessive genetic osteochondrodysplasia characterized by dysmorphism, spondyloepiphyseal dysplasia, nephrotic syndrome and frequently T cell immunodeficiency. Several hypotheses have been proposed to explain pathophysiology of the disease, however, the mechanism by which SMARCAL1 mutations cause the syndrome is elusive. Here, we generated a conditional SMARCAL1 knockdown model in iPSCs to mimic conditions associated with the severe form the disease. Using multiple cellular endpoints, we characterized this model for the presence of phenotypes linked to the replication caretaker role of SMARCAL1. Our data show that conditional knockdown of SMARCAL1 in human iPSCs induces replication-dependent and chronic accumulation of DNA damage triggering the DNA damage response. Furthermore, they indicate that accumulation of DNA damage and activation of the DNA damage response correlates with increased levels of R-loops and replication-transcription interference. Finally, we provide evidence that SMARCAL1-deficient iPSCs maintain DNA damage response active beyond differentiation, possibly contributing to the observed altered expression of a subset of germ layer-specific master genes. Confirming the relevance of SMARCAL1 loss for the observed phenotypes, they are prevented or rescued after re-expression of wild-type SMARCAL1 in our iPSC model. In conclusion, our conditional SMARCAL1 knockdown model in iPSCs may represent a powerful model where studying pathogenetic mechanisms of severe Schimke immuno-osseous dysplasia.

The coronavirus disease 2019 (COVID-19) pandemic has caused more than 2.3 million casualties worldwide and the lack of effective treatments is a major health concern. The development of targeted drugs is held back due to a limited understanding of the molecular mechanisms underlying the perturbation of cell physiology observed after viral infection. Recently, several approaches, aimed at identifying cellular proteins that may contribute to COVID-19 pathology, have been reported. Albeit valuable, this information offers limited mechanistic insight as these efforts have produced long lists of cellular proteins, the majority of which are not annotated to any cellular pathway. We have embarked in a project aimed at bridging this mechanistic gap by developing a new bioinformatic approach to estimate the functional distance between a subset of proteins and a list of pathways. A comprehensive literature search allowed us to annotate, in the SIGNOR 2.0 resource, causal information underlying the main molecular mechanisms through which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and related coronaviruses affect the host–cell physiology. Next, we developed a new strategy that enabled us to link SARS-CoV-2 interacting proteins to cellular phenotypes via paths of causal relationships. Remarkably, the extensive information about inhibitors of signaling proteins annotated in SIGNOR 2.0 makes it possible to formulate new potential therapeutic strategies. The proposed approach, which is generally applicable, generated a literature-based causal network that can be used as a framework to formulate informed mechanistic hypotheses on COVID-19 etiology and pathology.

FLT3 mutations are the most frequently identified genetic alterations in acute myeloid leukemia (AML) and are associated with poor clinical outcome, relapse and chemotherapeutic resistance. Elucidating the molecular mechanisms underlying FLT3-dependent pathogenesis and drug resistance is a crucial goal of biomedical research. Given the complexity and intricacy of protein signaling networks, deciphering the molecular basis of FLT3-driven drug resistance requires a systems approach. Here we discuss how the recent advances in mass spectrometry (MS)-based (phospho) proteomics and multiparametric analysis accompanied by emerging computational approaches offer a platform to obtain and systematically analyze cell-specific signaling networks and to identify new potential therapeutic targets.