Host factor prioritization for pan-viral genetic perturbation screens using random intercept models and network propagation

PLoS Computational Biology, vol. 16, pp. e1007587

Abstract

Genetic perturbation screens using RNA interference (RNAi) have been conducted successfully to identify host factors that are essential for the life cycle of bacteria or viruses. So far, most published studies identified host factors primarily for single pathogens. Furthermore, often only a small subset of genes, e.g., genes encoding kinases, have been targeted. Identification of host factors on a pan-pathogen level, i.e., genes that are crucial for the replication of a diverse group of pathogens has received relatively little attention, despite the fact that such common host factors would be highly relevant, for instance, for devising broad-spectrum anti-pathogenic drugs. Here, we present a novel two-stage procedure for the identification of host factors involved in the replication of different viruses using a combination of random effects models and Markov random walks on a functional interaction network. We first infer candidate genes by jointly analyzing multiple perturbations screens while at the same time adjusting for high variance inherent in these screens. Subsequently the inferred estimates are spread across a network of functional interactions thereby allowing for the analysis of missing genes in the biological studies, smoothing the effect sizes of previously found host factors, and considering a priori pathway information defined over edges of the network. We applied the procedure to RNAi screening data of four different positive-sense single-stranded RNA viruses, Hepatitis C virus, Chikungunya virus, Dengue virus and Severe acute respiratory syndrome coronavirus, and detected novel host factors, including UBC, PLCG1, and DYRK1B, which are predicted to significantly impact the replication cycles of these viruses. We validated the detected host factors experimentally using pharmacological inhibition and an additional siRNA screen and found that some of the predicted host factors indeed influence the replication of these pathogens.

Authors 10

1. Simon Dirmeier

   SIB Swiss Institute of Bioinformatics · ETH Zurich

   Affiliation as printed

   Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland

   SIB Swiss Institute of Bioinformatics, Basel, Switzerland

2. Christopher Dächert

   German Cancer Research Center · Heidelberg University

   Affiliation as printed

   Faculty of Biosciences, Heidelberg University, Heidelberg, Germany

   Research Group "Dynamics of Early Viral Infection and the Innate Antiviral Response" (division F170), German Cancer Research Center, Heidelberg, Germany

3. Martijn J. van Hemert Aachen Department of Medical Microbiology

   Leiden University Medical Center

   Affiliation as printed

   Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands

4. Ali Taş Aachen Department of Medical Microbiology

   Leiden University Medical Center

   Affiliation as printed

   Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands

5. Natacha S. Ogando Aachen Department of Medical Microbiology

   Leiden University Medical Center

   Affiliation as printed

   Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands

6. Frank J. M. van Kuppeveld

   Utrecht University

   Affiliation as printed

   Virology Division, Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands

7. Ralf F. W. Bartenschlager

   German Cancer Research Center · Heidelberg University

   Affiliation as printed

   Department for Infectious Diseases, Molecular Virology, Heidelberg University, Heidelberg, Germany

   Division Virus-Associated Carcinogenesis, German Cancer Research Center, Heidelberg, Germany

8. Lars Kaderali

   Universitätsmedizin Greifswald · Universität Greifswald

   Affiliation as printed

   University Medicine Greifswald, Institute of Bioinformatics, Greifswald, Germany

9. Marco Binder

   German Cancer Research Center

   Affiliation as printed

   Research Group "Dynamics of Early Viral Infection and the Innate Antiviral Response" (division F170), German Cancer Research Center, Heidelberg, Germany

10. Niko Beerenwinkel corresponding

    SIB Swiss Institute of Bioinformatics · ETH Zurich

    Affiliation as printed

    Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland

    SIB Swiss Institute of Bioinformatics, Basel, Switzerland