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Mechanism of cell lethality following loss of gene expression.

基因表达缺失后细胞致死的机制。

基本信息

批准号：
10751723
负责人：
Nicholas Wade Harper
金额：
$ 3.25万
依托单位：
UNIV OF MASSACHUSETTS MED SCH WORCESTER
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-08-01 至 2025-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10751723
关键词：
Accidents Alternative Splicing Apoptosis Apoptotic BCL2 gene Bcl-2 Homology Domain Binding CRISPR screen Cancerous Candidate Disease Gene Cell Death Cell Death Induction Cell Nucleus Cell physiology Cells Cessation of life Clinical Clustered Regularly Interspaced Short Palindromic Repeats Complex Consensus Cytoplasm DNA Polymerase II Data Death Rate Drug Design Experimental Genetics Family member Gene Expression Genes Genetic Transcription Goals Immunoprecipitation Knock-out Knowledge Measures Messenger RNA Methods Mitochondria Modeling Normal Cell Nuclear Nuclear Export Nuclear Protein Patient Selection Patients Pharmaceutical Preparations Phenotype Process Production Protein Isoforms Proteins RNA RNA Splicing RNA immunoprecipitation sequencing RNA-Binding Proteins Regulation Regulator Genes Resistance Role Series Signal Transduction Testing Time Toxic effect Transcript Work cancer cell cell growth cell killing cell type design drug mechanism experimental study genetic regulatory protein genome-wide improved inhibitor inhibitor therapy insight interest live cell imaging live cell microscopy mRNA Expression mRNA Precursor novel novel drug combination pre-clinical response treatment strategy

项目摘要

PROJECT SUMMARY The goal of this project is to determine the mechanism by which cell death results from transcriptional inhibition. The consensus model in the field posits that cell death following transcriptional inhibition results from the loss of specific mRNA species and subsequent loss of protein. By targeting such a core cellular process, transcriptional inhibition is thought to overwhelm cellular control and lead to unavoidable cell death. This death process, defined as Accidental Cell Death (ACD), is not controlled by the cell and does not result from the use of defined effector molecules. Contrary to the conventional model, we found that, rather than induce ACD, cell death following transcriptional inhibition results from a previously undescribed regulated apoptotic signal. Furthermore, we found that RNA Pol II degradation, rather than loss of mRNA production, resulted in cell death. Our data suggests a new model, whereby degradation of Pol II induces a signal that leaves the nucleus and is received by the mitochondria to initiate apoptosis. To identify genes that regulate a pro-apoptotic signal following transcriptional inhibition, we performed a genome-wide CRISPR screen. Genome-wide CRISPR screens often fail to identify death regulatory genes, making it difficult to elucidate mechanisms of cell death. To overcome this, we developed a novel experimental strategy that allowed us to identify genes whose knockout modulated the cell death rate following transcriptional inhibition. Based on the results of our screen, in Aim 1 we will test the hypothesis that the alternative splicing regulator PTBP1 facilitates altered splicing and nuclear export of regulatory pre-mRNA, and that this activity is required for cell death following transcriptional inhibition. We will use live cell microscopy to establish the functional role of PTBP1 nuclear export. We will use SLAM-seq and RIP-seq to quantify PTBP1 activity following transcriptional inhibition. Our screen also identified BCL2L12 as the critical apoptotic effector gene for transcriptional inhibition. In Aim 2, we will test the hypothesis that BCL2L12 activates apoptosis following transcriptional inhibition in an isoform-specific manner. We will perform a series of functional genetics experiments to characterize the role of BCL2L12 in the apoptotic response. By describing a new mechanistic model by which transcriptional inhibition induces cell death, we will improve our understanding of how to effectively use transcriptional inhibitors therapeutically. Ultimately, we hope our work will improve our ability to predict which patients will best respond to transcriptional inhibitors and help identify novel treatment strategies.

项目总结