Jue Fan

Abstract A newly identified coronavirus, 2019-nCoV, has been posing significant threats to public health since December 2019. ACE2, the host cell receptor for severe acute respiratory syndrome coronavirus (SARS), has recently been demonstrated in mediating 2019-nCoV infection. Interestingly, besides the respiratory system, substantial proportion of SARS and 2019-nCoV patients showed signs of various degrees of liver damage, the mechanism and implication of which have not yet been determined. Here, we performed an unbiased evaluation of cell type specific expression of ACE2 in healthy liver tissues using single cell RNA-seq data of two independent cohorts, and identified specific expression in cholangiocytes. The results indicated that virus might directly bind to ACE2 positive cholangiocytes but not necessarily hepatocytes. This finding suggested the liver abnormalities of SARS and 2019-nCoV patients may not be due to hepatocyte damage, but cholangiocyte dysfunction and other causes such as drug induced and systemic inflammatory response induced liver injury. Our findings indicate that special care of liver dysfunction should be installed in treating 2019-nCoV patients during the hospitalization and shortly after cure.

Lung cancer is a highly heterogeneous disease. Cancer cells and cells within the tumor microenvironment together determine disease progression, as well as response to or escape from treatment. To map the cell type-specific transcriptome landscape of cancer cells and their tumor microenvironment in advanced non-small cell lung cancer (NSCLC), we analyze 42 tissue biopsy samples from stage III/IV NSCLC patients by single cell RNA sequencing and present the large scale, single cell resolution profiles of advanced NSCLCs. In addition to cell types described in previous single cell studies of early stage lung cancer, we are able to identify rare cell types in tumors such as follicular dendritic cells and T helper 17 cells. Tumors from different patients display large heterogeneity in cellular composition, chromosomal structure, developmental trajectory, intercellular signaling network and phenotype dominance. Our study also reveals a correlation of tumor heterogeneity with tumor associated neutrophils, which might help to shed light on their function in NSCLC.

In Alzheimer's disease, accumulation of soluble oligomers of β-amyloid peptide is known to be highly toxic, causing disturbances in synaptic activity and neuronal death. Multiple studies relate these effects to increased oxidative stress and aberrant activity of calcium-permeable cation channels leading to calcium imbalance. The transient receptor potential melastatin 2 (TRPM2) channel, a Ca(2+)-permeable nonselective cation channel activated by oxidative stress, has been implicated in neurodegenerative diseases, and more recently in amyloid-induced toxicity. Here we show that the function of TRPM2 is augmented by treatment of cultured neurons with β-amyloid oligomers. Aged APP/PS1 Alzheimer's mouse model showed increased levels of endoplasmic reticulum stress markers, protein disulfide isomerase and phosphorylated eukaryotic initiation factor 2α, as well as decreased levels of the presynaptic marker synaptophysin. Elimination of TRPM2 in APP/PS1 mice corrected these abnormal responses without affecting plaque burden. These effects of TRPM2 seem to be selective for β-amyloid toxicity, as ER stress responses to thapsigargin or tunicamycin in TRPM2(-/-) neurons was identical to that of wild-type neurons. Moreover, reduced microglial activation was observed in TRPM2(-/-)/APP/PS1 hippocampus compared with APP/PS1 mice. In addition, age-dependent spatial memory deficits in APP/PS1 mice were reversed in TRPM2(-/-)/APP/PS1 mice. These results reveal the importance of TRPM2 for β-amyloid neuronal toxicity, suggesting that TRPM2 activity could be potentially targeted to improve outcomes in Alzheimer's disease. SIGNIFICANCE STATEMENT: Transient receptor potential melastatin 2 (TRPM2) is an oxidative stress sensing calcium-permeable channel that is thought to contribute to calcium dysregulation associated with neurodegenerative diseases, including Alzheimer's disease. Here we show that oligomeric β-amyloid, the toxic peptide in Alzheimer's disease, facilitates TRPM2 channel activation. In mice designed to model Alzheimer's disease, genetic elimination of TRPM2 normalized deficits in synaptic markers in aged mice. Moreover, the absence of TRPM2 improved age-dependent spatial memory deficits observed in Alzheimer's mice. Our results reveal the importance of TRPM2 for neuronal toxicity and memory impairments in an Alzheimer's mouse model and suggest that TRPM2 could be targeted for the development of therapeutic agents effective in the treatment of dementia.

Acetylcholine (ACh) is an important neuromodulator in the nervous system implicated in many forms of cognitive and motor processing. Recent studies have used bacterial artificial chromosome (BAC) transgenic mice expressing channelrhodopsin-2 (ChR2) protein under the control of the choline acetyltransferase (ChAT) promoter (ChAT-ChR2-EYFP) to dissect cholinergic circuit connectivity and function using optogenetic approaches. We report that a mouse line used for this purpose also carries several copies of the vesicular acetylcholine transporter gene (VAChT), which leads to overexpression of functional VAChT and consequently increased cholinergic tone. We demonstrate that these mice have marked improvement in motor endurance. However, they also present severe cognitive deficits, including attention deficits and dysfunction in working memory and spatial memory. These results suggest that increased VAChT expression may disrupt critical steps in information processing. Our studies demonstrate that ChAT-ChR2-EYFP mice show altered cholinergic tone that fundamentally differentiates them from wild-type mice.

Single-cell RNA sequencing (scRNA-seq) has been rapidly developing and widely applied in biological and medical research. Identification of cell types in scRNA-seq data sets is an essential step before in-depth investigations of their functional and pathological roles. However, the conventional workflow based on clustering and marker genes is not scalable for an increasingly large number of scRNA-seq data sets due to complicated procedures and manual annotation. Therefore, a number of tools have been developed recently to predict cell types in new data sets using reference data sets. These methods have not been generally adapted due to a lack of tool benchmarking and user guidance. In this article, we performed a comprehensive and impartial evaluation of nine classification software tools specifically designed for scRNA-seq data sets. Results showed that Seurat based on random forest, SingleR based on correlation analysis and CaSTLe based on XGBoost performed better than others. A simple ensemble voting of all tools can improve the predictive accuracy. Under nonideal situations, such as small-sized and class-imbalanced reference data sets, tools based on cluster-level similarities have superior performance. However, even with the function of assigning 'unassigned' labels, it is still challenging to catch novel cell types by solely using any of the single-cell classifiers. This article provides a guideline for researchers to select and apply suitable classification tools in their analysis workflows and sheds some lights on potential direction of future improvement on classification tools.