High-throughput platforms for genetic perturbation screening using CRISPR/Cas9 in human iPSC-derived macrophages for drug discovery
Year: 2026
Type: preprint
Abstract: Human induced Pluripotent Stem Cell (hiPSC) models have revolutionised drug discovery, offering high translational relevance for recapitulating disease biology and thereby the potential to help reduce drug attrition. Macrophages are pivotal for maintaining tissue homeostasis and orchestrating immune responses; their dysregulation underpins several diseases, including autoinflammatory disorders, neurodegeneration, and cancer. Therapeutically targeting this cell type presents an attractive strategy to simultaneously influence multiple cellular mediators and functions. We have established a scalable, semi-automated, and physiologically relevant hiPSC-derived macrophage model, rigorously characterised through deep comparative multi-omics. We have also integrated our hiPSC-derived macrophage platform with large-scale CRISPR screening workflows designed for parallel genetic interrogation of thousands of gene targets, in both arrayed and pooled formats. In this manuscript, we apply those genetic screening methods to hiPSC-derived macrophages and showcase how genetic perturbations alter pro- and anti-inflammatory transcriptional signatures and significantly impact functional phenotypes in this cell model. This integrated approach allows for the exploration of novel genetic insights linked to causal disease biology, advancing myeloid cell-associated target discovery across a broad spectrum of therapeutic areas.
Authors: Matteo Martufi, Eleni Karagianni, Tasos Papanikos, Tim Ashlin, Aikaterini Geladaki, Benedetta Carbone, Katja Remlinger, Andres Quintero Moreno, William Pembroke, Charlie Haslam, Nico Zinn, Denise Vlachou, Margarida Almeida, Dimitrios Tsaousis, Stephan Gade, Bin Sun, Muhammad Maqbool, Holger Franken, Frederik Ziebell, Alessandro Di Tullio, Lewis Entwistle, Naren Srinivasan, Mercedes Lobera, Lisa Mohamet
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7213356000