Dataset Information

In Vivo RNAi Screening Identifies MDA5 as a Significant Contributor to the Cellular Defense against Influenza A Virus.

ABSTRACT: Responding to an influenza A virus (IAV) infection demands an effective intrinsic cellular defense strategy to slow replication. To identify contributing host factors to this defense, we exploited the host microRNA pathway to perform an in vivo RNAi screen. To this end, IAV, lacking a functional NS1 antagonist, was engineered to encode individual siRNAs against antiviral host genes in an effort to rescue attenuation. This screening platform resulted in the enrichment of strains targeting virus-activated transcription factors, specific antiviral effectors, and intracellular pattern recognition receptors (PRRs). Interestingly, in addition to RIG-I, the PRR for IAV, a virus with the capacity to silence MDA5 also emerged as a dominant strain in wild-type, but not in MDA5-deficient mice. Transcriptional profiling of infected knockout cells confirmed RIG-I to be the primary PRR for IAV but implicated MDA5 as a significant contributor to the cellular defense against influenza A virus.

SUBMITTER: Benitez AA

PROVIDER: S-EPMC4586153 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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In Vivo RNAi Screening Identifies MDA5 as a Significant Contributor to the Cellular Defense against Influenza A Virus.

Benitez Asiel A AA Panis Maryline M Xue Jia J Varble Andrew A Shim Jaehee V JV Frick Amy L AL López Carolina B CB Sachs David D tenOever Benjamin R BR

Cell reports 20150611 11

Responding to an influenza A virus (IAV) infection demands an effective intrinsic cellular defense strategy to slow replication. To identify contributing host factors to this defense, we exploited the host microRNA pathway to perform an in vivo RNAi screen. To this end, IAV, lacking a functional NS1 antagonist, was engineered to encode individual siRNAs against antiviral host genes in an effort to rescue attenuation. This screening platform resulted in the enrichment of strains targeting virus-a ...[more]

PMID: 26074083

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Project description:BackgroundRNA interference (RNAi) becomes an increasingly important and effective genetic tool to study the function of target genes by suppressing specific genes of interest. This system approach helps identify signaling pathways and cellular phase types by tracking intensity and/or morphological changes of cells. The traditional RNAi screening scheme, in which one siRNA is designed to knockdown one specific mRNA target, needs a large library of siRNAs and turns out to be time-consuming and expensive.ResultsIn this paper, we propose a conceptual model, called compressed sensing RNAi (csRNAi), which employs a unique combination of group of small interfering RNAs (siRNAs) to knockdown a much larger size of genes. This strategy is based on the fact that one gene can be partially bound with several small interfering RNAs (siRNAs) and conversely, one siRNA can bind to a few genes with distinct binding affinity. This model constructs a multi-to-multi correspondence between siRNAs and their targets, with siRNAs much fewer than mRNA targets, compared with the conventional scheme. Mathematically this problem involves an underdetermined system of equations (linear or nonlinear), which is ill-posed in general. However, the recently developed compressed sensing (CS) theory can solve this problem. We present a mathematical model to describe the csRNAi system based on both CS theory and biological concerns. To build this model, we first search nucleotide motifs in a target gene set. Then we propose a machine learning based method to find the effective siRNAs with novel features, such as image features and speech features to describe an siRNA sequence. Numerical simulations show that we can reduce the siRNA library to one third of that in the conventional scheme. In addition, the features to describe siRNAs outperform the existing ones substantially.ConclusionsThis csRNAi system is very promising in saving both time and cost for large-scale RNAi screening experiments which may benefit the biological research with respect to cellular processes and pathways.

Dataset Information

In Vivo RNAi Screening Identifies MDA5 as a Significant Contributor to the Cellular Defense against Influenza A Virus.

Publications

In Vivo RNAi Screening Identifies MDA5 as a Significant Contributor to the Cellular Defense against Influenza A Virus.

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