Dual proteome-scale networks reveal cell-specific remodeling of the human interactome.

Thousands of interactions assemble proteins into modules that impart spatial and functional organization to the cellular proteome. Through affinity-purification mass spectrometry, we have created two proteome-scale, cell-line-specific interaction networks. The first, BioPlex 3.0, results from affinity purification of 10,128 human proteins-half the proteome-in 293T cells and includes 118,162 interactions among 14,586 proteins. The second results from 5,522 immunoprecipitations in HCT116 cells. These networks model the interactome whose structure encodes protein function, localization, and complex membership. Comparison across cell lines validates thousands of interactions and reveals extensive customization. Whereas shared interactions reside in core complexes and involve essential proteins, cell-specific interactions link these complexes, "rewiring" subnetworks within each cell's interactome. Interactions covary among proteins of shared function as the proteome remodels to produce each cell's phenotype. Viewable interactively online through BioPlexExplorer, these networks define principles of proteome organization and enable unknown protein characterization.

Modular Organization and Assembly of SWI/SNF Family Chromatin Remodeling Complexes.

Mammalian SWI/SNF (mSWI/SNF) ATP-dependent chromatin remodeling complexes are multi-subunit molecular machines that play vital roles in regulating genomic architecture and are frequently disrupted in human cancer and developmental disorders. To date, the modular organization and pathways of assembly of these chromatin regulators remain unknown, presenting a major barrier to structural and functional determination. Here, we elucidate the architecture and assembly pathway across three classes of mSWI/SNF complexes-canonical BRG1/BRM-associated factor (BAF), polybromo-associated BAF (PBAF), and newly defined ncBAF complexes-and define the requirement of each subunit for complex formation and stability. Using affinity purification of endogenous complexes from mammalian and Drosophila cells coupled with cross-linking mass spectrometry (CX-MS) and mutagenesis, we uncover three distinct and evolutionarily conserved modules, their organization, and the temporal incorporation of these modules into each complete mSWI/SNF complex class. Finally, we map human disease-associated mutations within subunits and modules, defining specific topological regions that are affected upon subunit perturbation.

Targeting CDK9 Reactivates Epigenetically Silenced Genes in Cancer.

Cyclin-dependent kinase 9 (CDK9) promotes transcriptional elongation through RNAPII pause release. We now report that CDK9 is also essential for maintaining gene silencing at heterochromatic loci. Through a live cell drug screen with genetic confirmation, we discovered that CDK9 inhibition reactivates epigenetically silenced genes in cancer, leading to restored tumor suppressor gene expression, cell differentiation, and activation of endogenous retrovirus genes. CDK9 inhibition dephosphorylates the SWI/SNF protein BRG1, which contributes to gene reactivation. By optimization through gene expression, we developed a highly selective CDK9 inhibitor (MC180295, IC50 = 5 nM) that has broad anti-cancer activity in vitro and is effective in in vivo cancer models. Additionally, CDK9 inhibition sensitizes to the immune checkpoint inhibitor α-PD-1 in vivo, making it an excellent target for epigenetic therapy of cancer.

Structure-function analysis of the SHOC2-MRAS-PP1C holophosphatase complex.

Receptor tyrosine kinase (RTK)-RAS signalling through the downstream mitogen-activated protein kinase (MAPK) cascade regulates cell proliferation and survival. The SHOC2-MRAS-PP1C holophosphatase complex functions as a key regulator of RTK-RAS signalling by removing an inhibitory phosphorylation event on the RAF family of proteins to potentiate MAPK signalling1. SHOC2 forms a ternary complex with MRAS and PP1C, and human germline gain-of-function mutations in this complex result in congenital RASopathy syndromes2-5. However, the structure and assembly of this complex are poorly understood. Here we use cryo-electron microscopy to resolve the structure of the SHOC2-MRAS-PP1C complex. We define the biophysical principles of holoenzyme interactions, elucidate the assembly order of the complex, and systematically interrogate the functional consequence of nearly all of the possible missense variants of SHOC2 through deep mutational scanning. We show that SHOC2 binds PP1C and MRAS through the concave surface of the leucine-rich repeat region and further engages PP1C through the N-terminal disordered region that contains a cryptic RVXF motif. Complex formation is initially mediated by interactions between SHOC2 and PP1C and is stabilized by the binding of GTP-loaded MRAS. These observations explain how mutant versions of SHOC2 in RASopathies and cancer stabilize the interactions of complex members to enhance holophosphatase activity. Together, this integrative structure-function model comprehensively defines key binding interactions within the SHOC2-MRAS-PP1C holophosphatase complex and will inform therapeutic development .

Binding of TMPRSS2-ERG to BAF Chromatin Remodeling Complexes Mediates Prostate Oncogenesis.

Chromosomal rearrangements resulting in the fusion of TMPRSS2, an androgen-regulated gene, and the ETS family transcription factor ERG occur in over half of prostate cancers. However, the mechanism by which ERG promotes oncogenic gene expression and proliferation remains incompletely understood. Here, we identify a binding interaction between ERG and the mammalian SWI/SNF (BAF) ATP-dependent chromatin remodeling complex, which is conserved among other oncogenic ETS factors, including ETV1, ETV4, and ETV5. We find that ERG drives genome-wide retargeting of BAF complexes in a manner dependent on binding of ERG to the ETS DNA motif. Moreover, ERG requires intact BAF complexes for chromatin occupancy and BAF complex ATPase activity for target gene regulation. In a prostate organoid model, BAF complexes are required for ERG-mediated basal-to-luminal transition, a hallmark of ERG activity in prostate cancer. These observations suggest a fundamental interdependence between ETS transcription factors and BAF chromatin remodeling complexes in cancer.

BioPlexR and BioPlexPy: integrated data products for the analysis of human protein interactions.

SUMMARY: The BioPlex project has created two proteome scale, cell-line-specific protein-protein interaction (PPI) networks: the first in 293T cells, including 120k interactions among 15k proteins; and the second in HCT116 cells, including 70k interactions between 10k proteins. Here, we describe programmatic access to the BioPlex PPI networks and integration with related resources from within R and Python. Besides PPI networks for 293T and HCT116 cells, this includes access to CORUM protein complex data, PFAM protein domain data, PDB protein structures, and transcriptome and proteome data for the two cell lines. The implemented functionality serves as a basis for integrative downstream analysis of BioPlex PPI data with domain-specific R and Python packages, including efficient execution of maximum scoring sub-network analysis, protein domain-domain association analysis, mapping of PPIs onto 3D protein structures and analysis of BioPlex PPIs at the interface of transcriptomic and proteomic data. AVAILABILITY AND IMPLEMENTATION: The BioPlex R package is available from Bioconductor (bioconductor.org/packages/BioPlex), and the BioPlex Python package is available from PyPI (pypi.org/project/bioplexpy). Applications and downstream analyses are available from GitHub (github.com/ccb-hms/BioPlexAnalysis).

Combined Spinal Epidural Technique for Labor Analgesia Does Not Delay Recognition of Epidural Catheter Failures: A Single-center Retrospective Cohort Survival Analysis.

BACKGROUND: It is unclear whether recognition of epidural catheter failures is delayed with combined spinal epidural technique (CSE) compared to traditional epidural technique (EPID) when used for labor analgesia. The authors hypothesized that recognition of failed catheters is not delayed by CSE. METHODS: Anesthetic, obstetric, and quality assurance records from 2,395 labor neuraxial procedures (1,440 CSE and 955 EPID) performed at Forsyth Medical Center (Winston-Salem, North Carolina) between June 30 and December 31, 2012, were retrospectively analyzed. The primary outcome was catheter survival (failure-free) time during labor analgesia. A proportional hazards model with the counting method was used to assess relationships between the techniques and survival (failure-free) time of catheters, while controlling for subjects' body mass index and providers' level of training in the final best-fit multivariable regression model. RESULTS: Cumulative incidence of epidural catheter failures was 6.6% for CSE and 11.6% for EPID (P = 0.001). In the multivariable regression model, catheters placed with CSE versus epidural were less likely to fail (hazard ratio, 0.58; 95% CI, 0.43 to 0.79; P = 0.0002) for labor analgesia. Among the catheters that failed, there was no overall difference in failure time course between the techniques (hazard ratio, 1.17; 95% CI, 0.89 to 1.54; P = 0.26) even though more failed catheters with CSE (48.4%) than with EPID (30.6%) were recognized within the first 30 min of placement (P = 0.009). CONCLUSIONS: In this cohort, CSE has a significantly lower risk of overall epidural catheter failures than EPID and does not delay recognition of epidural catheter failures. Choice of CSE versus EPID should be based on overall risk of failure, efficacy, and side effects.

On knowing a gene: A distributional hypothesis of gene function.

As words can have multiple meanings that depend on sentence context, genes can have various functions that depend on the surrounding biological system. This pleiotropic nature of gene function is limited by ontologies, which annotate gene functions without considering biological contexts. We contend that the gene function problem in genetics may be informed by recent technological leaps in natural language processing, in which representations of word semantics can be automatically learned from diverse language contexts. In contrast to efforts to model semantics as "is-a" relationships in the 1990s, modern distributional semantics represents words as vectors in a learned semantic space and fuels current advances in transformer-based models such as large language models and generative pre-trained transformers. A similar shift in thinking of gene functions as distributions over cellular contexts may enable a similar breakthrough in data-driven learning from large biological datasets to inform gene function.

Accurate proteome-wide missense variant effect prediction with AlphaMissense.

The vast majority of missense variants observed in the human genome are of unknown clinical significance. We present AlphaMissense, an adaptation of AlphaFold fine-tuned on human and primate variant population frequency databases to predict missense variant pathogenicity. By combining structural context and evolutionary conservation, our model achieves state-of-the-art results across a wide range of genetic and experimental benchmarks, all without explicitly training on such data. The average pathogenicity score of genes is also predictive for their cell essentiality, capable of identifying short essential genes that existing statistical approaches are underpowered to detect. As a resource to the community, we provide a database of predictions for all possible human single amino acid substitutions and classify 89% of missense variants as either likely benign or likely pathogenic.

Sparse dictionary learning recovers pleiotropy from human cell fitness screens.

In high-throughput functional genomic screens, each gene product is commonly assumed to exhibit a singular biological function within a defined protein complex or pathway. In practice, a single gene perturbation may induce multiple cascading functional outcomes, a genetic principle known as pleiotropy. Here, we model pleiotropy in fitness screen collections by representing each gene perturbation as the sum of multiple perturbations of biological functions, each harboring independent fitness effects inferred empirically from the data. Our approach (Webster) recovered pleiotropic functions for DNA damage proteins from genotoxic fitness screens, untangled distinct signaling pathways upstream of shared effector proteins from cancer cell fitness screens, and predicted the stoichiometry of an unknown protein complex subunit from fitness data alone. Modeling compound sensitivity profiles in terms of genetic functions recovered compound mechanisms of action. Our approach establishes a sparse approximation mechanism for unraveling complex genetic architectures underlying high-dimensional gene perturbation readouts.