Dataset Information

Sequencing Framework for the Sensitive Detection and Precise Mapping of Defective Interfering Particle-Associated Deletions across Influenza A and B Viruses.

ABSTRACT: The mechanisms and consequences of defective interfering particle (DIP) formation during influenza virus infection remain poorly understood. The development of next-generation sequencing (NGS) technologies has made it possible to identify large numbers of DIP-associated sequences, providing a powerful tool to better understand their biological relevance. However, NGS approaches pose numerous technical challenges, including the precise identification and mapping of deletion junctions in the presence of frequent mutation and base-calling errors, and the potential for numerous experimental and computational artifacts. Here, we detail an Illumina-based sequencing framework and bioinformatics pipeline capable of generating highly accurate and reproducible profiles of DIP-associated junction sequences. We use a combination of simulated and experimental control data sets to optimize pipeline performance and demonstrate the absence of significant artifacts. Finally, we use this optimized pipeline to reveal how the patterns of DIP-associated junction formation differ between different strains and subtypes of influenza A and B viruses and to demonstrate how these data can provide insight into mechanisms of DIP formation. Overall, this work provides a detailed roadmap for high-resolution profiling and analysis of DIP-associated sequences within influenza virus populations.IMPORTANCE Influenza virus defective interfering particles (DIPs) that harbor internal deletions within their genomes occur naturally during infection in humans and during cell culture. They have been hypothesized to influence the pathogenicity of the virus; however, their specific function remains elusive. The accurate detection of DIP-associated deletion junctions is crucial for understanding DIP biology but is complicated by an array of technical issues that can bias or confound results. Here, we demonstrate a combined experimental and computational framework for detecting DIP-associated deletion junctions using next-generation sequencing (NGS). We detail how to validate pipeline performance and provide the bioinformatics pipeline for groups interested in using it. Using this optimized pipeline, we detect hundreds of distinct deletion junctions generated during infection with a diverse panel of influenza viruses and use these data to test a long-standing hypothesis concerning the molecular details of DIP formation.

SUBMITTER: Alnaji FG

PROVIDER: S-EPMC6532088 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Sequencing Framework for the Sensitive Detection and Precise Mapping of Defective Interfering Particle-Associated Deletions across Influenza A and B Viruses.

Alnaji Fadi G FG Holmes Jessica R JR Rendon Gloria G Vera J Cristobal JC Fields Christopher J CJ Martin Brigitte E BE Brooke Christopher B CB

Journal of virology 20190515 11

The mechanisms and consequences of defective interfering particle (DIP) formation during influenza virus infection remain poorly understood. The development of next-generation sequencing (NGS) technologies has made it possible to identify large numbers of DIP-associated sequences, providing a powerful tool to better understand their biological relevance. However, NGS approaches pose numerous technical challenges, including the precise identification and mapping of deletion junctions in the prese ...[more]

PMID: 30867305

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Project description:Cell culture-derived defective interfering particles (DIPs) are considered for antiviral therapy due to their ability to inhibit influenza A virus (IAV) production. DIPs contain a large internal deletion in one of their eight viral RNAs (vRNAs) rendering them replication-incompetent. However, they can propagate alongside their homologous standard virus (STV) during infection in a competition for cellular and viral resources. So far, experimental and modeling studies for IAV have focused on either the intracellular or the cell population level when investigating the interaction of STVs and DIPs. To examine these levels simultaneously, we conducted a series of experiments using highly different multiplicities of infections for STVs and DIPs to characterize virus replication in Madin-Darby Canine Kidney suspension cells. At several time points post infection, we quantified virus titers, viable cell concentration, virus-induced apoptosis using imaging flow cytometry, and intracellular levels of vRNA and viral mRNA using real-time reverse transcription qPCR. Based on the obtained data, we developed a mathematical multiscale model of STV and DIP co-infection that describes dynamics closely for all scenarios with a single set of parameters. We show that applying high DIP concentrations can shut down STV propagation completely and prevent virus-induced apoptosis. Interestingly, the three observed viral mRNAs (full-length segment 1 and 5, defective interfering segment 1) accumulated to vastly different levels suggesting the interplay between an internal regulation mechanism and a growth advantage for shorter viral RNAs. Furthermore, model simulations predict that the concentration of DIPs should be at least 10000 times higher than that of STVs to prevent the spread of IAV. Ultimately, the model presented here supports a comprehensive understanding of the interactions between STVs and DIPs during co-infection providing an ideal platform for the prediction and optimization of vaccine manufacturing as well as DIP production for therapeutic use.

Project description:Defective interfering particles (DIPs) replicate at the expense of coinfecting, fully infectious homologous virus. Typically, they contain a highly deleted form of the viral genome. Utilizing single-cell analysis, here we report the discovery of a yet-unknown DIP type, derived from influenza A viruses (IAVs), termed OP7 virus. Instead of deletions, the genomic viral RNA (vRNA) of segment 7 (S7) carried 37 point mutations compared to the reference sequence, affecting promoter regions, encoded proteins, and genome packaging signals. Coinfection experiments demonstrated strong interference of OP7 virus with IAV replication, manifested by a dramatic decrease in the infectivity of released virions. Moreover, an overproportional quantity of S7 in relation to other genome segments was observed, both intracellularly and in the released virus population. Concurrently, OP7 virions lacked a large fraction of other vRNA segments, which appears to constitute its defect in virus replication. OP7 virus might serve as a promising candidate for antiviral therapy. Furthermore, this novel form of DIP may also be present in other IAV preparations.IMPORTANCE Defective interfering particles (DIPs) typically contain a highly deleted form of the viral genome, rendering them defective in virus replication. Yet upon complementation through coinfection with fully infectious standard virus (STV), interference with the viral life cycle can be observed, leading to suppressed STV replication and the release of mainly noninfectious DIPs. Interestingly, recent research indicates that DIPs may serve as an antiviral agent. Here we report the discovery of a yet-unknown type of influenza A virus-derived DIP (termed "OP7" virus) that contains numerous point mutations instead of large deletions in its genome. Furthermore, the underlying principles that render OP7 virions interfering and apparently defective seem to differ from those of conventional DIPs. In conclusion, we believe that OP7 virus might be a promising candidate for antiviral therapy. Moreover, it exerts strong effects, both on virus replication and on the host cell response, and may have been overlooked in other IAV preparations.

Dataset Information

Sequencing Framework for the Sensitive Detection and Precise Mapping of Defective Interfering Particle-Associated Deletions across Influenza A and B Viruses.

Publications

Sequencing Framework for the Sensitive Detection and Precise Mapping of Defective Interfering Particle-Associated Deletions across Influenza A and B Viruses.

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