Single-cell analysis of population context advances RNAi screening at multiple levels

A large set of high-content RNAi screens investigating mammalian virus infection and multiple cellular activities is analysed to reveal the impact of population context on phenotypic variability and to identify indirect RNAi effects.

Cell population context determines phenotypes in RNAi screens of multiple cellular activities (including virus infection, cell size regulation, endocytosis, and lipid homeostasis), which can be accounted for by a combination of novel image analysis and multivariate statistical methods.

Accounting for cell population context-mediated effects strongly changes the reproducibility and consistency of RNAi screens across cell lines as well as of siRNAs targeting the same gene.

Such analyses can identify the perturbed regulation of population context dependent cell-to-cell variability, a novel perturbation phenotype.

Overall, these methods advance the use of large-scale RNAi screening for a systems-level understanding of cellular processes.

Isogenic cells in culture show strong variability, which arises from dynamic adaptations to the microenvironment of individual cells. Here we study the influence of the cell population context, which determines a single cell's microenvironment, in image-based RNAi screens. We developed a comprehensive computational approach that employs Bayesian and multivariate methods at the single-cell level. We applied these methods to 45 RNA interference screens of various sizes, including 7 druggable genome and 2 genome-wide screens, analysing 17 different mammalian virus infections and four related cell physiological processes. Analysing cell-based screens at this depth reveals widespread RNAi-induced changes in the population context of individual cells leading to indirect RNAi effects, as well as perturbations of cell-to-cell variability regulators. We find that accounting for indirect effects improves the consistency between siRNAs targeted against the same gene, and between replicate RNAi screens performed in different cell lines, in different labs, and with different siRNA libraries. In an era where large-scale RNAi screens are increasingly performed to reach a systems-level understanding of cellular processes, we show that this is often improved by analyses that account for and incorporate the single-cell microenvironment.

Non-invasive imaging of mouse hepatitis coronavirus infection reveals determinants of viral replication and spread in vivo

Bioluminescence imaging (BLI) is a powerful new method to study virus dissemination in the live animal. Here we used this method to monitor the spatial and temporal progression of mouse hepatitis coronavirus (MHV) infection in mice using luciferase‐expressing viruses. Upon intranasal inoculation, virus replication could initially be observed in the nasal cavity and the cervical lymph nodes, after which the infection spread to the brain and frequently to the eyes. The kinetics of virus spread to and clearance from the brain appeared to depend on the inoculation dose. After intraperitoneal inoculation, virus replication was predominantly observed in the liver and occasionally in the intestines, but interestingly also in the tail and paws. BLI thus elucidated new anatomic locations of virus replication. Furthermore, MHV dissemination was shown to be critically depended on the viral spike protein, but also on the mouse strain used. Widespread dissemination was observed in mice lacking a functional type I interferon response. The importance of the type I interferon system in limiting viral spread was also demonstrated by the administration of type I interferons to mice. Our results provide new insights in coronavirus pathogenesis and demonstrate the potential of BLI to study coronavirus–host interactions in vivo.