DOT: a flexible multi-objective optimization framework for transferring features across single-cell and spatial omics.

Single-cell transcriptomics and spatially-resolved imaging/sequencing technologies have revolutionized biomedical research. However, they suffer from lack of spatial information and a trade-off of resolution and gene coverage, respectively. We propose DOT, a multi-objective optimization framework for transferring cellular features across these data modalities, thus integrating their complementary information. DOT uses genes beyond those common to the data modalities, exploits the local spatial context, transfers spatial features beyond cell-type information, and infers absolute/relative abundance of cell populations at tissue locations. Thus, DOT bridges single-cell transcriptomics data with both high- and low-resolution spatially-resolved data. Moreover, DOT combines practical aspects related to cell composition, heterogeneity, technical effects, and integration of prior knowledge. Our fast implementation based on the Frank-Wolfe algorithm achieves state-of-the-art or improved performance in localizing cell features in high- and low-resolution spatial data and estimating the expression of unmeasured genes in low-coverage spatial data.

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.

Biological plasticity rescues target activity in CRISPR knock outs.

Gene knock outs (KOs) are efficiently engineered through CRISPR-Cas9-induced frameshift mutations. While the efficiency of DNA editing is readily verified by DNA sequencing, a systematic understanding of the efficiency of protein elimination has been lacking. Here we devised an experimental strategy combining RNA sequencing and triple-stage mass spectrometry to characterize 193 genetically verified deletions targeting 136 distinct genes generated by CRISPR-induced frameshifts in HAP1 cells. We observed residual protein expression for about one third of the quantified targets, at variable levels from low to original, and identified two causal mechanisms, translation reinitiation leading to N-terminally truncated target proteins or skipping of the edited exon leading to protein isoforms with internal sequence deletions. Detailed analysis of three truncated targets, BRD4, DNMT1 and NGLY1, revealed partial preservation of protein function. Our results imply that systematic characterization of residual protein expression or function in CRISPR-Cas9-generated KO lines is necessary for phenotype interpretation.

The commonly used PI3-kinase probe LY294002 is an inhibitor of BET bromodomains.

A commonly used small-molecule probe in cell-signaling research is the phosphoinositide 3-kinase inhibitor LY294002. Quantitative chemoproteomic profiling shows that LY294002 and LY303511, a close analogue devoid of PI3K activity, inhibit the BET bromodomain proteins BRD2, BRD3, and BRD4 that comprise a family of targets structurally unrelated to PI3K. Both compounds competitively inhibit acetyl-lysine binding of the first but not the second bromodomain of BET proteins in cell extracts. X-ray crystallography shows that the chromen-4-one scaffold represents a new bromodomain pharmacophore and establishes LY294002 as a dual kinase and BET-bromodomain inhibitor, whereas LY303511 exhibits anti-inflammatory and antiproliferative effects similar to the recently discovered BET inhibitors.