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High-resolution CRISPR/Cas9 screens identify PAK2 as a suppressor of macrophage proliferation and macropinocytosis.

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NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE251887
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Macrophages play critical roles in immune function and are implicated as etiological agents in disease states such as cardiovascular disease and cancer. However, there is limited understanding of macrophage fitness molecular regulators, including survival, proliferation, and adhesion. This work identifies positive and negative regulators of macrophage fitness by harnessing the power of CRISPR/Cas9 whole genome screening technology. Here, we identified loss-of-function gene disruptions that caused mutant bone marrow-derived macrophages (BMDM) to decrease in culture abundance as supporters of macrophage fitness. Similarly, we identified genes that limit or suppress macrophage fitness by identifying those gene disruptions that caused BMDM to increase in abundance in cell culture. To do this, we analyzed the difference in frequency of sgRNA between the purified plasmid library used for lentiviral transfection versus the amplified sgRNA inserts from the DNA of BMDM following a 14-day post-viral transduction culture. With this approach, we identified gene disruptions to canonical essential genes, including previously described macrophage-specific essential genes such as Csf1r, as well as novel genes required for macrophage growth and survival. In addition, we also identified gene disruptions that increased macrophage abundance in culture, including canonical tumor suppressors such as p53 (Trp53) and cell cycle regulators (Cdkn1a/2a). Interestingly, targeting p21-activated kinase-2 (Pak2) led to those mutants becoming more productive, suggesting a novel role for Pak2 in suppressing macrophage fitness. Using targeted knockouts of PAK2, we show that PAK2 protein depletion affects NF2/Merlin-mediated downregulation of cyclin-d1. Further, this work indicates that PAK2 suppresses macropinocytic uptake in macrophages by modulating actin dynamics impacting pro-mitogenic signaling pathways downstream of macropinocytosis. Overall, this work shows how multiple pathways impact macrophage fitness and highlights the central role of PAK2 in macrophage fitness and macropinocytosis. Transgenic mice with a Rosa26-Cas9 knock-in on a C57BL/6J background were received from Jackson Laboratories (Stock No. 026179, Bar Harbor, ME). Mice were euthanized using CO2 inhalation and cervical dislocation, femurs were dissected from the mice, and bone marrow was harvested (Swanson, 1989) by flushing Dulbecco’s phosphate buffer saline (DPBS) without calcium or magnesium (GE Healthcare Life Sciences, Pittsburgh, PA) through the bone using a needle and syringe. Cells were plated in culture media containing 20% HI-FBS and 30% L-cell supernatant in high glucose DMEM in non-tissue culture-treated sterile dishes and incubated at 37°C with 5% CO2. Additional culture media was added to the cells on day two post-isolation. Following cell adherence to the dish, on day 4, the medium was removed entirely, and fresh BMM was added to the culture. On day five cells were treated with 10 mM Cyclosporin A for 20 minutes before adding lentivirus with Brie library to the cells. Multiplicity of infection (MOI) ~ 0.3-0.1. Library coverage was around 100-200-fold representation of each sgRNA. Transduced cells were antibiotic-selected two days after transduction with 5mg/mL puromycin. Cells were cultured for at least 14 days for protein depletion (post-culture). Genomic DNA was extracted from post-culture cells using the GeneJET genomic DNA extraction kit (#K0721 Thermofisher). The sgRNA inserts from genomic DNA (Post-culture) and library plasmid DNA (Input) were PCR amplified by a single-step PCR protocol (Broad Institute). Barcoded primers with staggered sequences are used for next-generation sequencing (NGS). Sequencing of 75 base reads was conducted on Illumina Nextseq 500. Following quality control analysis using FASTQC, reads were mapped to the sgRNA library to identify genes, and read frequency tables were generated using Model-based Analysis of Genome-wide CRISPR-Cas9 Knockouts (MAGeCK), version 0.5.9 (Li et al., 2014a).
创建时间:
2024-05-01
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