Accumulation and Phosphorylation of RecQ-Mediated Genome Instability Protein 1 (RMI1) at Serine 284 and Serine 292 during Mitosis

KNO1‐mediated autophagic degradation of the Bloom syndrome complex component RMI1 promotes homologous recombination

Homologous recombination (HR) is a key DNA damage repair pathway that is tightly adjusted to the state of a cell. A central regulator of homologous recombination is the conserved helicase-containing Bloom syndrome complex, renowned for its crucial role in maintaining genome integrity. Here, we show that in Arabidopsis thaliana, Bloom complex activity is controlled by selective autophagy. We find that the recently identified DNA damage regulator KNO1 facilitates K63-linked ubiquitination of RMI1, a structural component of the complex, thereby triggering RMI1 autophagic degradation and resulting in increased homologous recombination. Conversely, reduced autophagic activity makes plants hypersensitive to DNA damage. KNO1 itself is also controlled at the level of proteolysis, in this case mediated by the ubiquitin-proteasome system, becoming stabilized upon DNA damage via two redundantly acting deubiquitinases, UBP12 and UBP13. These findings uncover a regulatory cascade of selective and interconnected protein degradation steps resulting in a fine-tuned HR response upon DNA damage.

Discovery of a Novel Bloom's Syndrome Protein (BLM) Inhibitor Suppressing Growth and Metastasis of Prostate Cancer

Prostate cancer (PCa) is a common cancer and a major cause of cancer-related death worldwide in men, necessitating novel targets for cancer therapy. High expression of Bloom's syndrome protein (BLM) helicase is associated with the occurrence and development of PCa. Therefore, the identification and development of new BLM inhibitors may be a new direction for the treatment of PCa. Here, we identified a novel inhibitor by molecular docking and put it to systematic evaluation via various experiments, AO/854, which acted as a competitive inhibitor that blocked the BLM-DNA interaction. Cellular evaluation indicated that AO/854-suppressed tumor growth and metastasis in PC3 cells by enhancing DNA damage, phosphorylating Chk1/Chk2, and altering the p53 signaling pathway. Collectively, the study highlights the potential of BLM as a therapeutic target in PCa and reveals a distinct mechanism by which AO/854 competitively inhibits the function of BLM.

Virulent Mycobacterium avium subspecies hominissuis subverts macrophages during early stages of infection

Virulent non-tuberculous Mycobacteria (NTMs) successfully reside and multiply within the phagosomes of phagocytic cells such as monocytes and macrophages. Macrophages play a very important role in the innate clearance of intracellular pathogens including NTMs. Attenuated Mycobacterium avium subsp. hominissuis 100 enters macrophages but is incapable of escaping these cells via canonical mycobacteria escape mechanisms. Alternatively, virulent Mycobacterium avium subsp. hominissuis 104 and Mycobacterium abscessus subsp. abscessus are able to modify macrophages to suit their growth, survival and ultimately escape from macrophages, while non-virulent Mycobacterium smegmatis is readily killed by macrophages. In this study we focused on early infection of macrophages with NTMs to determine the phenotypic response of macrophages, M1 or M2 differentiation, and phosphorylation alterations that can affect cellular response to invading bacteria. Our findings indicate that infection of the macrophage with MAH 100 and M. smegmatis favours the development of M1 macrophage, a pro-inflammatory phenotype associated with the killing of intracellular pathogens, while infection of the macrophage with MAH 104 and M. abscessus favoured the development of M2 macrophage, an anti-inflammatory phenotype associated with the healing process. Interference with the host post-translational mechanisms, such as protein phosphorylation, is a key strategy used by many intracellular bacterial pathogens to modulate macrophage phenotype and subvert macrophage function. By comparing protein phosphorylation patterns of infected macrophages, we observed that uptake of both MAH 100 and M. smegmatis resulted in MARCKS-related protein phosphorylation, which has been associated with macrophage activation. In contrast, in macrophages infected with MAH 104 and M. abscessus, methionine adenosyltransferase IIβ, an enzyme that catalyses the biosynthesis of S-adenosylmethionine, a methyl donor for DNA methylation. Inhibition of DNA methylation with 5-aza-2 deoxycytidine, significantly impaired the survival of MAH 104 in macrophages. Our findings suggest that the virulent MAH 104 and M. abscessus enhance its survival in the macrophage possibly through interference with the epigenome responses.

Identification and external validation of a prognostic signature associated with DNA repair genes in gastric cancer

The aim of this study was to construct and validate a DNA repair-related gene signature for evaluating the overall survival (OS) of patients with gastric cancer (GC). Differentially expressed DNA repair genes between GC and normal gastric tissue samples obtained from the TCGA database were identified. Univariate Cox analysis was used to screen survival-related genes and multivariate Cox analysis was applied to construct a DNA repair-related gene signature. An integrated bioinformatics approach was performed to evaluate its diagnostic and prognostic value. The prognostic model and the expression levels of signature genes were validated using an independent external validation cohort. Two genes (CHAF1A, RMI1) were identified to establish the prognostic signature and patients ware stratified into high- and low-risk groups. Patients in high-risk group presented significant shorter survival time than patients in the low-risk group in both cohorts, which were verified by the ROC curves. Multivariate analysis showed that the prognostic signature was an independent predictor for patients with GC after adjustment for other known clinical parameters. A nomogram incorporating the signature and known clinical factors yielded better performance and net benefits in calibration plot and decision curve analyses. Further, the logistic regression classifier based on the two genes presented an excellent diagnostic power in differentiating early HCC and normal tissues with AUCs higher than 0.9. Moreover, Gene Set Enrichment Analysis revealed that diverse cancer-related pathways significantly clustered in the high-risk and low-risk groups. Immune cell infiltration analysis revealed that CHAF1A and RMI1 were correlated with several types of immune cell subtypes. A prognostic signature using CHAF1A and RMI1 was developed that effectively predicted different OS rates among patients with GC. This risk model provides new clinical evidence for the diagnostic accuracy and survival prediction of GC.

Identification and Bioinformatic Assessment of circRNA Expression After RMI1 Knockdown and Ionizing Radiation Exposure

RecQ-mediated genome instability protein 1 (RMI1) is an important component of the BLM-Topo IIIα-RMI1-RMI2 complex and plays a critical role in maintaining genome stability. However, the cellular functions of RMI1 in response to ionizing radiation (IR) are poorly understood. In this study, we found that RMI1 knockdown led to enhanced radiosensitivity and apoptosis after irradiation. To analyze the effect of RMI1 knockdown on the expression of circular RNAs (circRNAs), we performed high-throughput RNA sequencing on four groups of human embryonic kidney (HEK) 293T cells: control cells and RMI1 knockdown cells with or without IR exposure. A total of 179 and 160 differentially expressed circRNAs (DE-circRNAs) were identified under RMI1 knockdown without and with exposure to IR, respectively. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed that these DE-circRNAs were involved in a variety of functions and signal pathways, including histone H3-K36 methylation, nuclear pore organization, mRNA destabilization, the mismatch repair pathway, and the apoptotic signaling pathway. Overall, our results indicate that RMI1 plays a crucial role in the response to IR and, more generally, that circRNAs are important in the regulatory mechanism of the radiation response.

Bloom Syndrome Protein Activates AKT and PRAS40 in Prostate Cancer Cells

Purpose

Prostate cancer (PC) is a common malignant tumor and a leading cause of cancer-related death in men worldwide. In order to design new therapeutic interventions for PC, an understanding of the molecular events underlying PC tumorigenesis is required. Bloom syndrome protein (BLM) is a RecQ-like helicase, which helps maintain genetic stability. BLM dysfunction has been implicated in tumor development, most recently during PC tumorigenesis. However, the molecular basis for BLM-induced PC progression remains poorly characterized. In this study, we investigated whether BLM modulates the phosphorylation of an array of prooncogenic signaling pathways to promote PC progression.

Methods

We analyzed differentially expressed proteins (DEPs) using iTRAQ technology. Site-directed knockout of BLM in PC-3 prostate cancer cells was performed using CRISPR/Cas9-mediated homologous recombination gene editing to confirm the effects of BLM on DEPs. PathScan® Antibody Array Kits were used to analyze the phosphorylation of nodal proteins in PC tissue. Immunohistochemistry and automated western blot (WES) analyses were used to validate these findings.

Results

We found that silencing BLM in PC-3 cells significantly reduced their proliferative capacity. In addition, BLM downregulation significantly reduced levels of phosphorylated protein kinase B (AKT (Ser473)) and proline-rich AKT substrate of 40 kDa (PRAS40 (Thr246)), and this was accompanied by enhanced ROS (reactive oxygen species) levels. In addition, we found that AKT and PRAS40 inhibition reduced BLM, increased ROS levels, and induced PC cell apoptosis.

Conclusions

We demonstrated that BLM activates AKT and PRAS40 to promote PC cell proliferation and survival. We further propose that ROS act in concert with BLM to facilitate PC oncogenesis, potentially via further enhancing AKT signaling and downregulating PTEN expression. Importantly, inhibiting the BLM-AKT-PRAS40 axis induced PC cell apoptosis. Thus, we highlight new avenues for novel anti-PC treatments.

A novel method of using Deep Belief Networks and genetic perturbation data to search for yeast signaling pathways

Perturbing a signaling system with a serial of single gene deletions and then observing corresponding expression changes in model organisms, such as yeast, is an important and widely used experimental technique for studying signaling pathways. People have developed different computational methods to analyze the perturbation data from gene deletion experiments for exploring the signaling pathways. The most popular methods/techniques include K-means clustering and hierarchical clustering techniques, or combining the expression data with knowledge, such as protein-protein interactions (PPIs) or gene ontology (GO), to search for new pathways. However, these methods neither consider nor fully utilize the intrinsic relation between the perturbation of a pathway and expression changes of genes regulated by the pathway, which served as the main motivation for developing a new computational method in this study. In our new model, we first find gene transcriptomic modules such that genes in each module are highly likely to be regulated by a common signal. We then use the expression status of those modules as readouts of pathway perturbations to search for up-stream pathways. Systematic evaluation, such as through gene ontology enrichment analysis, has provided evidence that genes in each transcriptomic module are highly likely to be regulated by a common signal. The PPI density analysis and literature search revealed that our new perturbation modules are functionally coherent. For example, the literature search revealed that 9 genes in one of our perturbation module are related to cell cycle and all 10 genes in another perturbation module are related by DNA damage, with much evidence from the literature coming from in vitro or/and in vivo verifications. Hence, utilizing the intrinsic relation between the perturbation of a pathway and the expression changes of genes regulated by the pathway is a useful method of searching for signaling pathways using genetic perturbation data. This model would also be suitable for analyzing drug experiment data, such as the CMap data, for finding drugs that perturb the same pathways.