Network integration of thermal proteome profiling with multi-omics data decodes PARP inhibition.

Complex disease phenotypes often span multiple molecular processes. Functional characterization of these processes can shed light on disease mechanisms and drug effects. Thermal Proteome Profiling (TPP) is a mass-spectrometry (MS) based technique assessing changes in thermal protein stability that can serve as proxies of functional protein changes. These unique insights of TPP can complement those obtained by other omics technologies. Here, we show how TPP can be integrated with phosphoproteomics and transcriptomics in a network-based approach using COSMOS, a multi-omics integration framework, to provide an integrated view of transcription factors, kinases and proteins with altered thermal stability. This allowed us to recover consequences of Poly (ADP-ribose) polymerase (PARP) inhibition in ovarian cancer cells on cell cycle and DNA damage response as well as interferon and hippo signaling. We found that TPP offers a complementary perspective to other omics data modalities, and that its integration allowed us to obtain a more complete molecular overview of PARP inhibition. We anticipate that this strategy can be used to integrate functional proteomics with other omics to study molecular processes.

A Tandem Guide RNA-Based Strategy for Efficient CRISPR Gene Editing of Cell Populations with Low Heterogeneity of Edited Alleles.

CRISPR/Cas9-based gene knockouts (KOs) enable precise perturbation of target gene function in human cells, which is ideally assessed in an unbiased fashion by molecular omics readouts. Typically, this requires the lengthy process of isolating KO subclones. We show here that KO subclones are phenotypically heterogenous, regardless of the guide RNA used. We present an experimental strategy that avoids subcloning and achieves fast and efficient gene silencing on cell pools, based on the synergistic combination of two guide RNAs mapping at close (40-300 bp) genomic proximity. Our strategy results in better predictable indel generation with a low allelic heterogeneity, concomitant with low or undetectable residual target protein expression, as determined by MS3 mass spectrometry proteomics. Our method is compatible with nondividing primary cells and can also be used to study essential genes. It enables the generation of high confidence omics data which solely reflect the phenotype of the target ablation.