Ubiquitin Ligase COP1 Suppresses Neuroinflammation by Degrading c/EBPß in Microglia.

Dysregulated microglia are intimately involved in neurodegeneration, including Alzheimer's disease (AD) pathogenesis, but the mechanisms controlling pathogenic microglial gene expression remain poorly understood. The transcription factor CCAAT/enhancer binding protein beta (c/EBPß) regulates pro-inflammatory genes in microglia and is upregulated in AD. We show expression of c/EBPß in microglia is regulated post-translationally by the ubiquitin ligase COP1 (also called RFWD2). In the absence of COP1, c/EBPß accumulates rapidly and drives a potent pro-inflammatory and neurodegeneration-related gene program, evidenced by increased neurotoxicity in microglia-neuronal co-cultures. Antibody blocking studies reveal that neurotoxicity is almost entirely attributable to complement. Remarkably, loss of a single allele of Cebpb prevented the pro-inflammatory phenotype. COP1-deficient microglia markedly accelerated tau-mediated neurodegeneration in a mouse model where activated microglia play a deleterious role. Thus, COP1 is an important suppressor of pathogenic c/EBPß-dependent gene expression programs in microglia.

Massively parallel nanowell-based single-cell gene expression profiling.

BACKGROUND: Technological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable. RESULTS: Here we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5,184-nanowell-containing microchip to capture ~1,300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells. CONCLUSIONS: Overall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.