tetano
Editor, Senior Moderator
J Virol. 2014 Jun 25. pii: JVI.01494-14. [Epub ahead of print]
High-throughput identification of loss-of-function mutations for anti-interferon activity in influenza A virus NS segment.
Wu NC1, Young AP2, Al-Mawsawi LQ2, Olson CA2, Feng J2, Qi H2, Luan HH2, Li X3, Wu TT2, Sun R4.
Author information
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 fitness disadvantage in a specified growth condition. Our methodology is 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 on 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 (∼0.1-1%), which is usually higher than the occurrence frequency for individual point mutations within a mutant library. Therefore, only mutations that confer fitness advantage can be identified with confidence due to an enrichment in occurrence frequency. In contrast, it is impossible to identify deleterious mutations using most next-generation sequencing technique. 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 is involved in its anti-interferon activity.
Copyright ? 2014, American Society for Microbiology. All Rights Reserved.
PMID:
24965464
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/24965464
High-throughput identification of loss-of-function mutations for anti-interferon activity in influenza A virus NS segment.
Wu NC1, Young AP2, Al-Mawsawi LQ2, Olson CA2, Feng J2, Qi H2, Luan HH2, Li X3, Wu TT2, Sun R4.
Author information
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 fitness disadvantage in a specified growth condition. Our methodology is 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 on 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 (∼0.1-1%), which is usually higher than the occurrence frequency for individual point mutations within a mutant library. Therefore, only mutations that confer fitness advantage can be identified with confidence due to an enrichment in occurrence frequency. In contrast, it is impossible to identify deleterious mutations using most next-generation sequencing technique. 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 is involved in its anti-interferon activity.
Copyright ? 2014, American Society for Microbiology. All Rights Reserved.
PMID:
24965464
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/24965464