Dataset Information

Unraveling the Genome-Wide Impact of Recombinant Baculovirus Infection in Mammalian Cells for Gene Delivery.

ABSTRACT: Baculovirus expression systems have been widely used to produce recombinant mammalian proteins owing to the lack of viral replication in vertebrates. Although several lines of evidence have demonstrated impacts of baculovirus infection in mammalian hosts, genome-wide effects have not been fully elucidated. Here, we provide comparative transcriptome profiles of baculovirus and host-immune response genes in recombinant baculovirus-infected mammalian and insect cells. Specifically, to decipher the impacts of baculovirus infection in mammalian cells, we conducted total RNA-seq on human 293TT cells and insect Sf9 cells infected with recombinant baculovirus. We found that baculovirus genes were rarely expressed under the control of baculoviral promoters in 293TT cells. Although some baculovirus early genes, such as PE38 and IE-01, showed limited expression in 293TT cells, baculoviral late genes were mostly silent. We also found modest induction of a small number of mammalian immune response genes associated with Toll-like receptors, cytokine signaling, and complement in baculovirus-infected 293TT cells. These comprehensive transcriptome data will contribute to improving recombinant baculovirus as tools for gene delivery, gene therapy, and vaccine development.

SUBMITTER: Shin HY

PROVIDER: S-EPMC7694231 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Unraveling the Genome-Wide Impact of Recombinant Baculovirus Infection in Mammalian Cells for Gene Delivery.

Shin Ha Youn HY Choi Hanul H Kim Nahyun N Park Nayoung N Kim Heesun H Kim Jaebum J Kim Young Bong YB

Genes 20201104 11

Baculovirus expression systems have been widely used to produce recombinant mammalian proteins owing to the lack of viral replication in vertebrates. Although several lines of evidence have demonstrated impacts of baculovirus infection in mammalian hosts, genome-wide effects have not been fully elucidated. Here, we provide comparative transcriptome profiles of baculovirus and host-immune response genes in recombinant baculovirus-infected mammalian and insect cells. Specifically, to decipher the ...[more]

PMID: 33158084

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Project description:The function of the majority of genes in the human and mouse genomes is unknown. Investigating and illuminating this dark genome is a major challenge for the biomedical sciences. The International Mouse Phenotyping Consortium (IMPC) is addressing this through the generation and broad-based phenotyping of a knockout (KO) mouse line for every protein-coding gene, producing a multidimensional data set that underlies a genome-wide annotation map from genes to phenotypes. Here, we develop a multivariate (MV) statistical approach and apply it to IMPC data comprising 148 phenotypes measured across 4,548 KO lines. There are 4,256 (1.4% of 302,997 observed data measurements) hits called by the univariate (UV) model analysing each phenotype separately, compared to 31,843 (10.5%) hits in the observed data results of the MV model, corresponding to an estimated 7.5-fold increase in power of the MV model relative to the UV model. One key property of the data set is its 55.0% rate of missingness, resulting from quality control filters and incomplete measurement of some KO lines. This raises the question of whether it is possible to infer perturbations at phenotype-gene pairs at which data are not available, i.e., to infer some in vivo effects using statistical analysis rather than experimentation. We demonstrate that, even at missing phenotypes, the MV model can detect perturbations with power comparable to the single-phenotype analysis, thereby filling in the complete gene-phenotype map with good sensitivity. A factor analysis of the MV model's fitted covariance structure identifies 20 clusters of phenotypes, with each cluster tending to be perturbed collectively. These factors cumulatively explain 75% of the KO-induced variation in the data and facilitate biological interpretation of perturbations. We also demonstrate that the MV approach strengthens the correspondence between IMPC phenotypes and existing gene annotation databases. Analysis of a subset of KO lines measured in replicate across multiple laboratories confirms that the MV model increases power with high replicability.

Dataset Information

Unraveling the Genome-Wide Impact of Recombinant Baculovirus Infection in Mammalian Cells for Gene Delivery.

Publications

Unraveling the Genome-Wide Impact of Recombinant Baculovirus Infection in Mammalian Cells for Gene Delivery.

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