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High-throughput identification of loss-of-function mutations for anti-interferon activity in the influenza A virus NS segment
- Source :
- Journal of virology, vol 88, iss 17
- Publication Year :
- 2014
-
Abstract
- Viral proteins often display several functions which require multiple assays to dissect their genetic basis. Here, we describe a systematic approach to screen for loss-of-function mutations that confer a fitness disadvantage under a specified growth condition. Our methodology was achieved by genetically monitoring a mutant library under two growth conditions, with and without interferon, by deep sequencing. We employed a molecular tagging technique to distinguish true mutations from sequencing error. This approach enabled us to identify mutations that were negatively selected against, in addition to those that were positively selected for. Using this technique, we identified loss-of-function mutations in the influenza A virus NS segment that were sensitive to type I interferon in a high-throughput fashion. Mechanistic characterization further showed that a single substitution, D92Y, resulted in the inability of NS to inhibit RIG-I ubiquitination. The approach described in this study can be applied under any specified condition for any virus that can be genetically manipulated. IMPORTANCE Traditional genetics focuses on a single genotype-phenotype relationship, whereas high-throughput genetics permits phenotypic characterization of numerous mutants in parallel. High-throughput genetics often involves monitoring of a mutant library with deep sequencing. However, deep sequencing suffers from a high error rate (∼0.1 to 1%), which is usually higher than the occurrence frequency for individual point mutations within a mutant library. Therefore, only mutations that confer a fitness advantage can be identified with confidence due to an enrichment in the occurrence frequency. In contrast, it is impossible to identify deleterious mutations using most next-generation sequencing techniques. In this study, we have applied a molecular tagging technique to distinguish true mutations from sequencing errors. It enabled us to identify mutations that underwent negative selection, in addition to mutations that experienced positive selection. This study provides a proof of concept by screening for loss-of-function mutations on the influenza A virus NS segment that are involved in its anti-interferon activity.
- Subjects :
- Immunology
Mutant
Biology
Viral Nonstructural Proteins
medicine.disease_cause
Medical and Health Sciences
Microbiology
Deep sequencing
Vaccine Related
Negative selection
Virology
Genetics
medicine
Influenza A virus
Viral
Molecular Biology
Loss function
Mutation
Agricultural and Veterinary Sciences
Prevention
Point mutation
High-Throughput Nucleotide Sequencing
Biological Sciences
Virus-Cell Interactions
Emerging Infectious Diseases
Infectious Diseases
Insect Science
Interferon Type I
RNA
RNA, Viral
Interferon type I
Biotechnology
medicine.drug
Subjects
Details
- ISSN :
- 10985514
- Volume :
- 88
- Issue :
- 17
- Database :
- OpenAIRE
- Journal :
- Journal of virology
- Accession number :
- edsair.doi.dedup.....d234285df7c6e73128d9c30503db8665