Bao Tran

Loss of BRCA2 (breast cancer 2) is lethal for normal cells. Yet it remains poorly understood how, in BRCA2 mutation carriers, cells undergoing loss of heterozygosity overcome the lethality and undergo tissue-specific neoplastic transformation. Here, we identified mismatch repair gene mutL homolog 1 ( MLH1 ) as a genetic interactor of BRCA2 whose overexpression supports the viability of Brca2- null cells. Mechanistically, we showed that MLH1 interacts with Flap endonuclease 1 (FEN1) and competes to process the RNA flaps of Okazaki fragments. Together, they restrained the DNA2 nuclease activity on the reversed forks of lagging strands, leading to replication fork (RF) stability in BRCA2-deficient cells. In these cells, MLH1 also attenuated R-loops, allowing the progression of stable RFs, which suppressed genomic instability and supported cell viability. We demonstrated the significance of their genetic interaction by the lethality of Brca2 -mutant mice and inhibition of Brca2 -deficient tumor growth in mice by Mlh1 loss. Furthermore, we described estrogen as inducing MLH1 expression through estrogen receptor α (ERα), which might explain why the majority of BRCA2 mutation carriers develop ER-positive breast cancer. Taken together, our findings reveal a role of MLH1 in relieving replicative stress and show how it may contribute to the establishment of BRCA2-deficient breast tumors.

Epithelial ovarian cancer (EOC) remains the fifth leading cause of cancer-related death in women worldwide, partly due to the survival of chemoresistant, stem-like tumor-initiating cells (TICs) that promote disease relapse. We previously described a role for the NF-κB pathway in promoting TIC chemoresistance and survival through NF-κB transcription factors (TFs) RelA and RelB, which regulate genes important for the inflammatory response and those associated with cancer, including microRNAs (miRNAs). We hypothesized that NF-κB signaling differentially regulates miRNA expression through RelA and RelB to support TIC persistence. Inducible shRNA was stably expressed in OV90 cells to knockdown RELA or RELB; miR-seq analyses identified differentially expressed miRNAs hsa-miR-452-5p and hsa-miR-335-5p in cells grown in TIC versus adherent conditions. We validated the miR-seq findings via qPCR in TIC or adherent conditions with RELA or RELB knocked-down. We confirmed decreased expression of hsa-miR-452-5p when either RELA or RELB were depleted and increased expression of hsa-miR-335-5p when RELA was depleted. Either inhibiting miR-452-5p or mimicking miR-335-5p functionally decreased the stem-like potential of the TICs. These results highlight a novel role of NF-κB TFs in modulating miRNA expression in EOC cells, thus opening a better understanding toward preventing recurrence of EOC.

Herpes simplex virus type 2 (HSV-2) is a common causative agent of genital tract infections. Moreover, HSV-2 and HIV infection can mutually increase the risk of acquiring another virus infection. Due to the high GC content and highly repetitive regions in HSV-2 genomes, only the genomes of four strains have been completely sequenced (HG52, 333, SD90e, and MS). Strain G is commonly used for HSV-2 research, but only a partial genome sequence has been assembled with Illumina sequencing reads. In the current study, we de novo assembled and annotated the complete genome of strain G using PacBio long sequencing reads, which can span the repetitive regions, analyzed the ‘α’ sequence, which plays key roles in HSV-2 genome circulation, replication, cleavage, and packaging of progeny viral DNA, identified the packaging signals homologous to HSV-1 within the ‘α’ sequence, and determined both termini of the linear genome and cleavage site for the process of concatemeric HSV-2 DNA produced via rolling-circle replication. In addition, using Oxford Nanopore Technology sequencing reads, we visualized four HSV-2 genome isomers at the nucleotide level for the first time. Furthermore, the coding sequences of HSV-2 strain G have been compared with those of HG52, 333, and MS. Moreover, phylogenetic analysis of strain G and other diverse HSV-2 strains has been conducted to determine their evolutionary relationship. The results will aid clinical research and treatment development of HSV-2.

ATAC-seq (assay for transposase-accessible chromatin with high-throughput sequencing) is a powerful method to evaluate chromatin accessibility and nucleosome positioning at a genome-wide scale. This assay uses a hyperactive Tn5 transposase, to simultaneously cut open chromatin and insert adapter sequences. After sequencing, the reads generated through this technique are generally indicative of transcriptional regulatory elements that are located in accessible chromatin. This method was originally developed by Buenrostro et al. (2013), and since then it has been improved by the same authors several times, until their last update called OMNI ATAC-seq (Corces et al., 2017). Here, we describe an ATAC-seq protocol based on the OMNI-ATAC method, with a special focus on the initial steps of thawing cryopreserved cells, and the final steps of library purification using magnetic beads. This protocol can be of interest for laboratories working in a fast-paced environment.Graphic Flowchart of the protocol

Disease recurrence is the major cause of morbidity and mortality of ovarian cancer (OC). In terms of maintenance therapies after platinum-based chemotherapy, PARP inhibitors significantly improve the overall survival of patients with BRCA mutations but is of little benefit to patients without homologous recombination deficiency (HRD). The stem-like tumor-initiating cell (TIC) population within OC tumors are thought to contribute to disease recurrence and chemoresistance. Therefore, there is a need to identify drugs that target TICs to prevent relapse in OC without HRD. RNA sequencing analysis of OC cells grown in TIC conditions revealed a strong enrichment of genes involved in drug metabolism, oxidative phosphorylation and reactive oxygen species (ROS) pathways. Concurrently, a high-throughput drug screen identified drugs that showed efficacy against OC cells grown as TICs compared to adherent cells. Four drugs were chosen that affected drug metabolism and ROS response: disulfiram, bardoxolone methyl, elesclomol and salinomycin. The drugs were tested in vitro for effects on viability, sphere formation and markers of stemness CD133 and ALDH in TICs compared to adherent cells. The compounds promoted ROS accumulation and oxidative stress and disulfiram, elesclomol and salinomycin increased cell death following carboplatin treatment compared to carboplatin alone. Disulfiram and salinomycin were effective in a post-surgery, post-chemotherapy OC relapse model in vivo, demonstrating that enhancing oxidative stress in TICs can prevent OC recurrence.

Single-cell RNA sequencing (scRNA-seq) has become a very powerful technology for biomedical research and is becoming much more affordable as methods continue to evolve, but it is unknown how reproducible different platforms are using different bioinformatics pipelines, particularly the recently developed scRNA-seq batch correction algorithms. We carried out a comprehensive multi-center cross-platform comparison on different scRNA-seq platforms using standard reference samples. We compared six pre-processing pipelines, seven bioinformatics normalization procedures, and seven batch effect correction methods including CCA, MNN, Scanorama, BBKNN, Harmony, limma and ComBat to evaluate the performance and reproducibility of 20 scRNA-seq data sets derived from four different platforms and centers. We benchmarked scRNA-seq performance across different platforms and testing sites using global gene expression profiles as well as some cell-type specific marker genes. We showed that there were large batch effects; and the reproducibility of scRNA-seq across platforms was dictated both by the expression level of genes selected and the batch correction methods used. We found that CCA, MNN, and BBKNN all corrected the batch variations fairly well for the scRNA-seq data derived from biologically similar samples across platforms/sites. However, for the scRNA-seq data derived from or consisting of biologically distinct samples, limma and ComBat failed to correct batch effects, whereas CCA over-corrected the batch effect and misclassified the cell types and samples. In contrast, MNN, Harmony and BBKNN separated biologically different samples/cell types into correspondingly distinct dimensional subspaces; however, consistent with this algorithm’s logic, MNN required that the samples evaluated each contain a shared portion of highly similar cells. In summary, we found a great cross-platform consistency in separating two distinct samples when an appropriate batch correction method was used. We hope this large cross-platform/site scRNA-seq data set will provide a valuable resource, and that our findings will offer useful advice for the single-cell sequencing community.