Droplet-based microfluidic devices have become widely used to perform single-cell RNA sequencing (scRNA-seq). However, ambient RNA present in the cell suspension can be aberrantly counted along with a cell's native mRNA and result in cross-contamination of transcripts between different cell populations. DecontX is a novel Bayesian method to estimate and remove contamination in individual cells. DecontX accurately predicts contamination levels in a mouse-human mixture dataset and removes aberrant expression of marker genes in PBMC datasets. We also compare the contamination levels between four different scRNA-seq protocols. Overall, DecontX can be incorporated into scRNA-seq workflows to improve downstream analyses.

Little evidence is available regarding the physiological effects of exposure to electronic cigarette (ECIG) aerosol. We sought to determine the molecular impact of ECIG aerosol exposure in human bronchial epithelial cells (HBECs). Gene-expression profiling was conducted in primary grown at air liquid interface and exposed to 1 of 4 different ECIG aerosols, traditional tobacco cigarette (TCIG) smoke, or clean air. Findings were validated experimentally with quantitative polymerase chain reaction and a reactive oxygen species immunoassay. Using gene set enrichment analysis, signatures of in vitro ECIG exposure were compared with those generated from bronchial epithelial brushings of current TCIG smokers and former TCIG smokers currently using ECIGs. We found 546 genes differentially expressed across the ECIG, TCIG, and air-exposed groups of HBECs (ANOVA; FDR q < .05; fold change > 1.5). A subset of these changes were shared between TCIG- and ECIG-exposed HBECs. ECIG exposure induced genes involved in oxidative and xenobiotic stress pathways and increased a marker of reactive oxygen species production in a dose-dependent manner. ECIG exposure decreased expression of genes involved in cilia assembly and movement. Furthermore, gene-expression differences observed in vitro were concordant with differences observed in airway epithelium collected from ECIG users (q < .01). In summary, our data suggest that ECIG aerosol can induce gene-expression changes in bronchial airway epithelium in vitro, some of which are shared with TCIG smoke. These changes were generally less pronounced than the effects of TCIG exposure and were more pronounced in ECIG products containing nicotine than those without nicotine. Our data further suggest that the gene-expression alterations seen with the in vitro exposure system reflects the physiological effects experienced in vivo by ECIG users.

Droplet-based microfluidic devices have become widely used to perform single-cell RNA sequencing (scRNAseq) and discover novel cellular heterogeneity in complex biological systems. However, ambient RNA present in the cell suspension can be incorporated into these droplets and aberrantly counted along with a cell's native mRNA. This results in cross-contamination of transcripts between di↵erent cell populations and can potentially decrease the precision of downstream analyses. We developed a novel hierarchical Bayesian method called DecontX to estimate and remove contamination in individual cells from scRNAseq data. DecontX accurately predicted the proportion of contaminated counts in a mixture of mouse and human cells. Decontamination of PBMC datasets removed aberrant expression of cell type specific marker genes from other cell types and improved overall separation of cell clusters. In general, DecontX can be incorporated into scRNA-seq workflows to assess quality of dissociation protocols and improve downstream analyses.

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Single-cell RNA-seq (scRNA-seq) has emerged as a powerful technique to quantify gene expression in individual cells and to elucidate the molecular and cellular building blocks of complex tissues. We developed a novel Bayesian hierarchical model called Cellular Latent Dirichlet Allocation (Celda) to perform co-clustering of genes into transcriptional modules and cells into subpopulations. Celda can quantify the probabilistic contribution of each gene to each module, each module to each cell population and each cell population to each sample. In a peripheral blood mononuclear cell dataset, Celda identified a subpopulation of proliferating T cells and a plasma cell which were missed by two other common single-cell workflows. Celda also identified transcriptional modules that could be used to characterize unique and shared biological programs across cell types. Finally, Celda outperformed other approaches for clustering genes into modules on simulated data. Celda presents a novel method for characterizing transcriptional programs and cellular heterogeneity in scRNA-seq data.

Rationale: Recent epidemiological studies show that Diesel Engine Exhaust (DEE) exposure is associated with lung cancer, however the mechanism by which this occurs is not well understood. The goal of this study was to assess the transcriptomic alterations in the nasal epithelium of DEE exposed workers from factories where diesel engines are utilized. Methods: Nasal epithelium brushings were obtained from 41 subjects who work in a factory with DEE exposure, and 38 comparable control subjects who work in factories without any DEE exposure. The median Elemental Carbon (EC) levels of exposed individuals was 60.7μg/m3, with a range of 17.2-105.4 μg/m3, respectively. RNA was isolated from nasal epithelial cells, and profiled for gene expression using Affymetrix microarrays. Linear modeling was used to detect differential expression between DEE exposure and controls. Pathway enrichment in differentially expressed genes was assessed using GO Biological Process and KEGG terms via EnrichR. Results: We found 234 genes that were differentially expressed between samples derived from DEE exposed participants versus controls at FDR q &lt; 0.25. Within this set of genes, we observed a higher expression of genes involved in oxidative stress response, as well as cell proliferation, cellular transcription, and regulation of apoptosis. In addition, we found that genes involved in ion transport, such as CFTR, were expressed at lower levels in DEE exposed samples. Conclusions: Chronic DEE exposure associates with changes in the airway transcriptome, with increased stress response as a major effect of DEE exposure. The transcriptomic alterations we identified may help provide insight into the underlying mechanisms of DEE carcinogenicity. Citation Format: Eduard I. Drizik, Sean Corbett, Roel Vermeulen, Yufei Dai, Wei Hu, Marc Lenburg, Dianzhi Ren, Huawei Duan, Yong Niu, Jun Xu, Wei Fu, Kees Meliefste, Baosen Zhou, JuFang Yang, Meng Ye, Xiaowei Jia, Tao Meng, Ping Bin, Yuxin Zheng, Debra Silverman, Nathaniel Rothman, Avrum Spira, Qing Lan. Impact of diesel engine exhaust exposure on the airway transcriptome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4256. doi:10.1158/1538-7445.AM2017-4256

Electronic cigarettes (ECIGs) are an emerging alternative tobacco product thought by some to potentially be safer than traditional tobacco cigarettes (TCIGs). Despite the increasing prevalence of ECIG use, few studies have evaluated the potential physiological effects of ECIG exposure. In this study we aimed to determine the global gene expression effects of ECIG exposure on bronchial epithelium in vitro. Human bronchial epithelial cells (HBECs) grown at Air Liquid Interface (ALI) were exposed to TCIG smoke and ECIG vapor derived from tobacco or menthol flavored products with and without nicotine. We identified a number of gene expression alterations that were induced by both ECIG and TCIG exposure as well as a novel set of changes uniquely induced by ECIG exposure. ECIG exposure induced the expression of genes involved in oxidative and xenobiotic stress pathways and increased the production of reactive oxygen species, similar to, but generally lower in magnitude than, the effects of TCIGs. Furthermore, TCIG and ECIG exposure both decreased the expression of genes involved in cilia assembly and movement, suggesting that the integrity of the bronchial epithelium is concordantly impaired by both exposures. We additionally identified a number of ECIG-specific cell cycle and cell division pathway changes. Finally, we observed that ECIG-induced changes were dependent on both flavor and nicotine content. Together, these results indicate that ECIG vapor can induce cellular stress and molecular alterations within airway epithelium that share similarities with the effects of TCIG smoke. Based on these findings, further studies are warranted to determine whether ECIG use will lead to similar deleterious health outcomes as those caused by TCIGs. Citation Format: Elizabeth Moses, Teresa Wang, George R. Jackson, Sean Corbett, Eduard Drizik, Daniel Brooks, George O’Connor, Catalina Perdomo, Steven Dubinett, Patrick Hayden, Marc E. Lenburg, Avrum Spira. Molecular impact of in vitro exposure to electronic cigarette vapor in human bronchial epithelium. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4502.