MicroRNA-focused CRISPR/Cas9 screen identifies miR-142 as a key regulator of Epstein-Barr virus reactivation.

Reactivation from latency plays a significant role in maintaining persistent lifelong Epstein-Barr virus (EBV) infection. Mechanisms governing successful activation and progression of the EBV lytic phase are not fully understood. EBV expresses multiple viral microRNAs (miRNAs) and manipulates several cellular miRNAs to support viral infection. To gain insight into the host miRNAs regulating transitions from EBV latency into the lytic stage, we conducted a CRISPR/Cas9-based screen in EBV+ Burkitt lymphoma (BL) cells using anti-Ig antibodies to crosslink the B cell receptor (BCR) and induce reactivation. Using a gRNA library against >1500 annotated human miRNAs, we identified miR-142 as a key regulator of EBV reactivation. Genetic ablation of miR-142 enhanced levels of immediate early and early lytic gene products in infected BL cells. Ago2-PAR-CLIP experiments with reactivated cells revealed miR-142 targets related to Erk/MAPK signaling, including components directly downstream of the B cell receptor (BCR). Consistent with these findings, disruption of miR-142 enhanced SOS1 levels and Mek phosphorylation in response to surface Ig cross-linking. Effects could be rescued by inhibitors of Mek (cobimetinib) or Raf (dabrafenib). Taken together, these results show that miR-142 functionally regulates SOS1/Ras/Raf/Mek/Erk signaling initiated through the BCR and consequently, restricts EBV entry into the lytic cycle.

Classifying polycyclic aromatic hydrocarbons by carcinogenic potency using in vitro biosignatures.

One of the most difficult challenges for risk assessment is evaluation of chemicals that predominately co-occur in mixtures like polycyclic aromatic hydrocarbons (PAHs). We previously developed a classification model in which systems biology data collected from mice short-term after chemical exposure accurately predict tumor outcome. The present study demonstrates translation of this approach into a human in vitro model in which chemical-specific bioactivity profiles from 3D human bronchial epithelial cells (HBEC) classify PAHs by carcinogenic potency. Gene expression profiles were analyzed from HBEC exposed to carcinogenic and non-carcinogenic PAHs and classification accuracies were identified for individual pathway-based gene sets. Posterior probabilities of best performing gene sets were combined via Bayesian integration resulting in a classifier with four gene sets, including aryl hydrocarbon receptor signaling, regulation of epithelial mesenchymal transition, regulation of angiogenesis, and cell cycle G2-M. In addition, transcriptional benchmark dose modeling of benzo[a]pyrene (BAP) showed that the most sensitive gene sets to BAP regulation were largely dissimilar from those that best classified PAH carcinogenicity challenging current assumptions that BAP carcinogenicity (and subsequent mode of action) is reflective of overall PAH carcinogenicity. These results illustrate utility of using systems toxicology approaches to analyze global gene expression towards carcinogenic hazard assessment.