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TMT-based quantitative proteomics analysis reveals the new regulatory mechanism of PGRN in influenza virus infection

ABSTRACT: To gain insight into the potential molecular mechanisms by which PGRN regulates influenza viral replication, proteomic analyses of whole mouse lung tissue from wild-type (WT) versus (vs) PGRN knockout (KO) mice were performed to identify proteins regulated by the absence vs presence of PGRN.

ORGANISM(S): Mus Musculus

SUBMITTER: Fanhua Wei

PROVIDER: PXD038885 | iProX | Mon Dec 19 00:00:00 GMT 2022

REPOSITORIES: iProX

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Tandem mass tag-based quantitative proteomics analysis reveals the new regulatory mechanism of progranulin in influenza virus infection.

Li Haoning H Zhang Yuying Y Li Chengye C Ning Peng P Sun Hailiang H Wei Fanhua F

Frontiers in microbiology 20230112

Progranulin (PGRN) plays an important role in influenza virus infection. To gain insight into the potential molecular mechanisms by which PGRN regulates influenza viral replication, proteomic analyzes of whole mouse lung tissue from wild-type (WT) versus (<i>vs</i>) PGRN knockout (KO) mice were performed to identify proteins regulated by the absence vs. presence of PGRN. Our results revealed that PGRN regulated the differential expression of ALOX15, CD14, CD5L, and FCER1g, etc., and also affecte ...[more]

PMID: 36713155

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Project description:Heldt2012 - Influenza Virus Replication The model describes the life cycle of influenza A virus in a mammalian cell including the following steps: attachment of parental virions to the cell membrane, receptor-mediated endocytosis, fusion of the virus envelope with the endosomal membrane, nuclear import of vRNPs, viral transcription and replication, translation of the structural viral proteins, nuclear export of progeny vRNPs and budding of new virions. It also explicitly accounts for the stabilization of cRNA by viral polymerases and NP and the inhibition of vRNP activity by M1 protein binding. In short, the model focuses on the molecular mechanism that controls viral transcription and replication. This model is described in the article: Modeling the intracellular dynamics of influenza virus replication to understand the control of viral RNA synthesis. Heldt FS, Frensing T, Reichl U. J Virol. Abstract: Influenza viruses transcribe and replicate their negative-sense RNA genome inside the nucleus of host cells via three viral RNA species. In the course of an infection, these RNAs show distinct dynamics, suggesting that differential regulation takes place. To investigate this regulation in a systematic way, we developed a mathematical model of influenza virus infection at the level of a single mammalian cell. It accounts for key steps of the viral life cycle, from virus entry to progeny virion release, while focusing in particular on the molecular mechanisms that control viral transcription and replication. We therefore explicitly consider the nuclear export of viral genome copies (vRNPs) and a recent hypothesis proposing that replicative intermediates (cRNA) are stabilized by the viral polymerase complex and the nucleoprotein (NP). Together, both mechanisms allow the model to capture a variety of published data sets at an unprecedented level of detail. Our findings provide theoretical support for an early regulation of replication by cRNA stabilization. However, they also suggest that the matrix protein 1 (M1) controls viral RNA levels in the late phase of infection as part of its role during the nuclear export of viral genome copies. Moreover, simulations show an accumulation of viral proteins and RNA toward the end of infection, indicating that transport processes or budding limits virion release. Thus, our mathematical model provides an ideal platform for a systematic and quantitative evaluation of influenza virus replication and its complex regulation. With the current parameter set, the model reproduces an infection at a multiplicity of infection (MOI) of 10. Figure 2A of the paper is reproduced here, with parameters kDegRnp and kSynP changed to zeros. Initial conditions and parameter changes that were used to obtain specific figures in the article can be found in Table A2. The model has the correct value for kAttLo as 4.55e-04. The value of this parameter mentioned as 4.55e-02 in Table 1 of the paper is incorrect. This is checked with the author. This model is hosted on BioModels Database and identified by: MODEL1307270000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

TMT-based quantitative proteomics analysis reveals the new regulatory mechanism of PGRN in influenza virus infection

Publications

Tandem mass tag-based quantitative proteomics analysis reveals the new regulatory mechanism of progranulin in influenza virus infection.

Similar Datasets

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