DJ-1 protects cell death from a mitochondrial oxidative stress due to GBA1 deficiency.

BACKGROUND: GBA1 mutations are the most common genetic risk factor for development of Parkinson's disease (PD). The loss of catalytic activity in GBA1, as well as the reduction of the GBA1 protein in certain cellular compartment, may increase disease progression. However, the mechanisms underlying cellular dysfunction caused by GBA1 deficiency are still mostly unknown. OBJECTIVE: In this study, we focus on the genetic interaction between GBA1 deficiency and PD-causing genes, such as DJ-1, in mitochondrial dysfunction. METHODS: GBA1 knockout (KO) SH-SY5Y cells were used to assess DJ-1 functions against oxidative stress in vitro. The levels of cellular reactive oxygen species were monitored with MitoSOX reagent. The expression of the PARK7 gene was analyzed using the quantitative real-time PCR (qRT-PCR). To understand the mechanism underlying DJ-1 upregulation in GBA1 KO cells, we assess ROS levels, antioxidant protein, and cell viability in GBA1 KO cells with treatment of ROS inhibitor N-acetyl-cysteine or miglustat, which is an inhibitor of glucosylceramide synthase. Dopaminergic degeneration was assessed from Gba1 L444P heterozygous mice mated with Park7 knockout mice. RESULTS: We find that DJ-1 is significantly upregulated in GBA1 KO cells. Elevated levels of DJ-1 are attributed to the transcriptional expression of PARK7 mRNA, but not the inhibition of DJ-1 protein degradation. Because DJ-1 expression is highly linked to oxidative stress, we observe cellular reactive oxygen species (ROS) in GBA1 KO cells. Moreover, several antioxidant gene expressions and protein levels are increased in GBA1 KO cells. To this end, GBA1 KO cells are more susceptible to H2O2-induced cell death. Importantly, there is a significant reduction in dopaminergic neurons in the midbrain from Gba1 L444P heterozygous mice mated with Park7 knockout mice, followed by mild motor dysfunction. CONCLUSION: Taken together, our results suggest that DJ-1 upregulation due to GBA1 deficiency has a protective role against oxidative stress. It may be supposed that mutations or malfunctions in the DJ-1 protein may have disadvantages in the survival of dopaminergic neurons in the brains of patients harboring GBA1 mutations.

Tracing oncogene-driven remodelling of the intestinal stem cell niche.

Interactions between tumour cells and the surrounding microenvironment contribute to tumour progression, metastasis and recurrence1-3. Although mosaic analyses in Drosophila have advanced our understanding of such interactions4,5, it has been difficult to engineer parallel approaches in vertebrates. Here we present an oncogene-associated, multicolour reporter mouse model-the Red2Onco system-that allows differential tracing of mutant and wild-type cells in the same tissue. By applying this system to the small intestine, we show that oncogene-expressing mutant crypts alter the cellular organization of neighbouring wild-type crypts, thereby driving accelerated clonal drift. Crypts that express oncogenic KRAS or PI3K secrete BMP ligands that suppress local stem cell activity, while changes in PDGFRloCD81+ stromal cells induced by crypts with oncogenic PI3K alter the WNT signalling environment. Together, these results show how oncogene-driven paracrine remodelling creates a niche environment that is detrimental to the maintenance of wild-type tissue, promoting field transformation dominated by oncogenic clones.

Single-cell RNA sequencing identifies shared differentiation paths of mouse thymic innate T cells.

Invariant natural killer T (iNKT), mucosal-associated invariant T (MAIT), and γδ T cells are innate T cells that acquire memory phenotype in the thymus and share similar biological characteristics. However, how their effector differentiation is developmentally regulated is still unclear. Here, we identify analogous effector subsets of these three innate T cell types in the thymus that share transcriptional profiles. Using single-cell RNA sequencing, we show that iNKT, MAIT and γδ T cells mature via shared, branched differentiation rather than linear maturation or TCR-mediated instruction. Simultaneous TCR clonotyping analysis reveals that thymic maturation of all three types is accompanied by clonal selection and expansion. Analyses of mice deficient of TBET, GATA3 or RORγt and additional in vivo experiments corroborate the predicted differentiation paths, while human innate T cells from liver samples display similar features. Collectively, our data indicate that innate T cells share effector differentiation processes in the thymus.

Correction to: PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas.

An amendment to this paper has been published and can be accessed via the original article.

PiggyBac mutagenesis and exome sequencing identify genetic driver landscapes and potential therapeutic targets of EGFR-mutant gliomas.

BACKGROUND: Glioma is the most common intrinsic brain tumor and also occurs in the spinal cord. Activating EGFR mutations are common in IDH1 wild-type gliomas. However, the cooperative partners of EGFR driving gliomagenesis remain poorly understood. RESULTS: We explore EGFR-mutant glioma evolution in conditional mutant mice by whole-exome sequencing, transposon mutagenesis forward genetic screening, and transcriptomics. We show mutant EGFR is sufficient to initiate gliomagenesis in vivo, both in the brain and spinal cord. We identify significantly recurrent somatic alterations in these gliomas including mutant EGFR amplifications and Sub1, Trp53, and Tead2 loss-of-function mutations. Comprehensive functional characterization of 96 gliomas by genome-wide piggyBac insertional mutagenesis in vivo identifies 281 known and novel EGFR-cooperating driver genes, including Cdkn2a, Nf1, Spred1, and Nav3. Transcriptomics confirms transposon-mediated effects on expression of these genes. We validate the clinical relevance of new putative tumor suppressors by showing these are frequently altered in patients' gliomas, with prognostic implications. We discover shared and distinct driver mutations in brain and spinal gliomas and confirm in vivo differential tumor suppressive effects of Pten between these tumors. Functional validation with CRISPR-Cas9-induced mutations in novel genes Tead2, Spred1, and Nav3 demonstrates heightened EGFRvIII-glioma cell proliferation. Chemogenomic analysis of mutated glioma genes reveals potential drug targets, with several investigational drugs showing efficacy in vitro. CONCLUSION: Our work elucidates functional driver landscapes of EGFR-mutant gliomas, uncovering potential therapeutic strategies, and provides new tools for functional interrogation of gliomagenesis.

Defining the Identity and Dynamics of Adult Gastric Isthmus Stem Cells.

The gastric corpus epithelium is the thickest part of the gastrointestinal tract and is rapidly turned over. Several markers have been proposed for gastric corpus stem cells in both isthmus and base regions. However, the identity of isthmus stem cells (IsthSCs) and the interaction between distinct stem cell populations is still under debate. Here, based on unbiased genetic labeling and biophysical modeling, we show that corpus glands are compartmentalized into two independent zones, with slow-cycling stem cells maintaining the base and actively cycling stem cells maintaining the pit-isthmus-neck region through a process of "punctuated" neutral drift dynamics. Independent lineage tracing based on Stmn1 and Ki67 expression confirmed that rapidly cycling IsthSCs maintain the pit-isthmus-neck region. Finally, single-cell RNA sequencing (RNA-seq) analysis is used to define the molecular identity and lineage relationship of a single, cycling, IsthSC population. These observations define the identity and functional behavior of IsthSCs.

Analysis of Technical and Biological Variability in Single-Cell RNA Sequencing.

Profiling the transcriptomes of individual cells with single-cell RNA sequencing (scRNA-seq) has been widely applied to provide a detailed molecular characterization of cellular heterogeneity within a population of cells. Despite recent technological advances of scRNA-seq, technical variability of gene expression in scRNA-seq is still much higher than that in bulk RNA-seq. Accounting for technical variability is therefore a prerequisite for correctly analyzing single-cell data. This chapter describes a computational pipeline for detecting highly variable genes exhibiting higher cell-to-cell variability than expected by technical noise. The basic pipeline using the scater and scran R/Bioconductor packages includes deconvolution-based normalization, fitting the mean-variance trend, testing for nonzero biological variability, and visualization with highly variable genes. An outline of the underlying theory of detecting highly variable genes is also presented. We illustrate how the pipeline works by using two case studies, one from mouse embryonic stem cells with external RNA spike-ins, and the other from mouse dentate gyrus cells without spike-ins.