Exploring the Functional Heterogeneity of Directly Reprogrammed Neural Stem Cell-Derived Neurons via Single-Cell RNA Sequencing.

The therapeutic potential of directly reprogrammed neural stem cells (iNSCs) for neurodegenerative diseases relies on reducing the innate tumorigenicity of pluripotent stem cells. However, the heterogeneity within iNSCs is a major hurdle in quality control prior to clinical applications. Herein, we generated iNSCs from human fibroblasts, by transfecting transcription factors using Sendai virus particles, and characterized the expression of iNSC markers. Using immunostaining and quantitative real time -polymerase chain reaction (RT -qPCR), no differences were observed between colonies of iNSCs and iNSC-derived neurons. Unexpectedly, patch-clamp analysis of iNSC-derived neurons revealed distinctive action potential firing even within the same batch product. We performed single-cell RNA sequencing in fibroblasts, iNSCs, and iNSC-derived neurons to dissect their functional heterogeneity and identify cell fate regulators during direct reprogramming followed by neuronal differentiation. Pseudotime trajectory analysis revealed distinct cell types depending on their gene expression profiles. Differential gene expression analysis showed distinct NEUROG1, PEG3, and STMN2 expression patterns in iNSCs and iNSC-derived neurons. Taken together, we recommend performing a predictable functional assessment with appropriate surrogate markers to ensure the quality control of iNSCs and their differentiated neurons, particularly before cell banking for regenerative cell therapy.

SIRT1 ubiquitination is regulated by opposing activities of APC/C-Cdh1 and AROS during stress-induced premature senescence.

SIRT1, a member of the mammalian sirtuin family, is a nicotinamide adenosine dinucleotide (NAD)-dependent deacetylase with key roles in aging-related diseases and cellular senescence. However, the mechanism by which SIRT1 protein homeostasis is controlled under senescent conditions remains elusive. Here, we revealed that SIRT1 protein is significantly downregulated due to ubiquitin-mediated proteasomal degradation during stress-induced premature senescence (SIPS) and that SIRT1 physically associates with anaphase-promoting complex/cyclosome (APC/C), a multisubunit E3 ubiquitin ligase. Ubiquitin-dependent SIRT1 degradation is stimulated by the APC/C coactivator Cdh1 and not by the coactivator Cdc20. We found that Cdh1 depletion impaired the SIPS-promoted downregulation of SIRT1 expression and reduced cellular senescence, likely through SIRT1-driven p53 inactivation. In contrast, AROS, a SIRT1 activator, reversed the SIRT1 degradation induced by diverse stressors and antagonized Cdh1 function through competitive interactions with SIRT1. Furthermore, our data indicate opposite roles for Cdh1 and AROS in the epigenetic regulation of the senescence-associated secretory phenotype genes IL-6 and IL-8. Finally, we demonstrated that pinosylvin restores downregulated AROS (and SIRT1) expression levels in bleomycin-induced mouse pulmonary senescent tissue while repressing bleomycin-promoted Cdh1 expression. Overall, our study provides the first evidence of the reciprocal regulation of SIRT1 stability by APC/C-Cdh1 and AROS during stress-induced premature senescence, and our findings suggest pinosylvin as a potential senolytic agent for pulmonary fibrosis.

TNF-α increases the intrinsic excitability of cerebellar Purkinje cells through elevating glutamate release in Bergmann Glia.

For decades, the glial function has been highlighted not only as the 'structural glue', but also as an 'active participant' in neural circuits. Here, we suggest that tumor necrosis factor α (TNF-α), a key inflammatory cytokine, alters the neural activity of the cerebellar Purkinje cells (PCs) by facilitating gliotransmission in the juvenile male rat cerebellum. A bath application of TNF-α (100 ng/ml) in acute cerebellar slices elevates spiking activity of PCs with no alterations in the regularity of PC firings. Interestingly, the effect of TNF-α on the intrinsic excitability of PCs was abolished under a condition in which the type1 TNF receptor (TNFR1) in Bergmann glia (BG) was genetically suppressed by viral delivery of an adeno-associated virus (AAV) containing TNFR1-shRNA. In addition, we measured the concentration of glutamate derived from dissociated cerebellar cortical astrocyte cultures treated with TNF-α and observed a progressive increase of glutamate in a time-dependent manner. We hypothesised that TNF-α-induced elevation of glutamate from BGs enveloping the synaptic cleft may directly activate metabotropic glutamate receptor1 (mGluR1). Pharmacological inhibition of mGluR1, indeed, prevented the TNF-α-mediated elevation of the intrinsic excitability in PCs. Taken together, our study reveals that TNF-α triggers glutamate release in BG, thereby increasing the intrinsic excitability of cerebellar PCs in a mGluR1-dependent manner.

Prognostic DNA methylation biomarkers in ovarian cancer.

PURPOSE: Aberrant DNA methylation, now recognized as a contributing factor to neoplasia, often shows definitive gene/sequence preferences unique to specific cancer types. Correspondingly, distinct combinations of methylated loci can function as biomarkers for numerous clinical correlates of ovarian and other cancers. EXPERIMENTAL DESIGN: We used a microarray approach to identify methylated loci prognostic for reduced progression-free survival (PFS) in advanced ovarian cancer patients. Two data set classification algorithms, Significance Analysis of Microarray and Prediction Analysis of Microarray, successfully identified 220 candidate PFS-discriminatory methylated loci. Of those, 112 were found capable of predicting PFS with 95% accuracy, by Prediction Analysis of Microarray, using an independent set of 40 advanced ovarian tumors (from 20 short-PFS and 20 long-PFS patients, respectively). Additionally, we showed the use of these predictive loci using two bioinformatics machine-learning algorithms, Support Vector Machine and Multilayer Perceptron. CONCLUSION: In this report, we show that highly prognostic DNA methylation biomarkers can be successfully identified and characterized, using previously unused, rigorous classifying algorithms. Such ovarian cancer biomarkers represent a promising approach for the assessment and management of this devastating disease.