Abstract
As key executers of biological functions, the activity and abundance of proteins are subjected to extensive regulation. Deciphering the genetic architecture underlying this regulation is critical for understanding cellular signalling events and responses to environmental cues. Using random mutagenesis in haploid human cells, we apply a sensitive approach to directly couple genomic mutations to protein measurements in individual cells. Here we use this to examine a suite of cellular processes, such as transcriptional induction, regulation of protein abundance and splicing, signalling cascades (mitogen-activated protein kinase (MAPK), G-protein-coupled receptor (GPCR), protein kinase B (AKT), interferon, and Wingless and Int-related protein (WNT) pathways) and epigenetic modifications (histone crotonylation and methylation). This scalable, sequencing-based procedure elucidates the genetic landscapes that control protein states, identifying genes that cause very narrow phenotypic effects and genes that lead to broad phenotypic consequences. The resulting genetic wiring map identifies the E3-ligase substrate adaptor KCTD5 (ref. 1) as a negative regulator of the AKT pathway, a key signalling cascade frequently deregulated in cancer. KCTD5-deficient cells show elevated levels of phospho-AKT at S473 that could not be attributed to effects on canonical pathway components. To reveal the genetic requirements for this phenotype, we iteratively analysed the regulatory network linked to AKT activity in the knockout background. This genetic modifier screen exposes suppressors of the KCTD5 phenotype and mechanistically demonstrates that KCTD5 acts as an off-switch for GPCR signalling by triggering proteolysis of Gβγ heterodimers dissociated from the Gα subunit. Although biological networks have previously been constructed on the basis of gene expression, protein-protein associations, or genetic interaction profiles, we foresee that the approach described here will enable the generation of a comprehensive genetic wiring map for human cells on the basis of quantitative protein states.