Illumina-based sequencing framework for accurate detection and mapping of influenza virus defective interfering particle-associated RNAs

AbstractThe 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 datasets to optimize pipeline performance and demonstrate the absence of significant artifacts. Finally, we use this optimized pipeline to generate a high-resolution profile of DIP-associated junctions produced during influenza virus infection and demonstrate how this data can provide insight into mechanisms of DIP formation. This work highlights the specific challenges associated with NGS-based detection of DIP-associated sequences, and details the computational and experimental controls required for such studies.

Download Full-text

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

Journal of Virology ◽

10.1128/jvi.00354-19 ◽

2019 ◽

Vol 93 (11) ◽

Cited By ~ 16

Author(s):

Fadi G. Alnaji ◽

Jessica R. Holmes ◽

Gloria Rendon ◽

J. Cristobal Vera ◽

Christopher J. Fields ◽

...

Keyword(s):

Influenza Virus ◽

Next Generation Sequencing ◽

Influenza A ◽

Influenza Viruses ◽

Next Generation ◽

Bioinformatics Pipeline ◽

Associated Sequences ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing ◽

Defective Interfering Particle

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.

Download Full-text

Host factors involved in influenza virus infection

Emerging Topics in Life Sciences ◽

10.1042/etls20200232 ◽

2020 ◽

Vol 4 (4) ◽

pp. 401-410

Author(s):

Matloob Husain

Keyword(s):

Influenza Virus ◽

Plasma Membrane ◽

Life Cycle ◽

Virus Infection ◽

Mammalian Cells ◽

Influenza Virus Infection ◽

Host Factors ◽

Tremendous Amount ◽

Human Viruses ◽

Insight Into

Influenza virus causes an acute febrile respiratory disease in humans that is commonly known as ‘flu’. Influenza virus has been around for centuries and is one of the most successful, and consequently most studied human viruses. This has generated tremendous amount of data and information, thus it is pertinent to summarise these for, particularly interdisciplinary readers. Viruses are acellular organisms and exist at the interface of living and non-living. Due to this unique characteristic, viruses require another organism, i.e. host to survive. Viruses multiply inside the host cell and are obligate intracellular pathogens, because their relationship with the host is almost always harmful to host. In mammalian cells, the life cycle of a virus, including influenza is divided into five main steps: attachment, entry, synthesis, assembly and release. To complete these steps, some viruses, e.g. influenza utilise all three parts — plasma membrane, cytoplasm and nucleus, of the cell; whereas others, e.g. SARS-CoV-2 utilise only plasma membrane and cytoplasm. Hence, viruses interact with numerous host factors to complete their life cycle, and these interactions are either exploitative or antagonistic in nature. The host factors involved in the life cycle of a virus could be divided in two broad categories — proviral and antiviral. This perspective has endeavoured to assimilate the information about the host factors which promote and suppress influenza virus infection. Furthermore, an insight into host factors that play a dual role during infection or contribute to influenza virus-host adaptation and disease severity has also been provided.

Download Full-text