Site-Specific Reversible Protein and Peptide Modification: Transglutaminase-Catalyzed Glutamine Conjugation and Bioorthogonal Light-Mediated Removal.

Dynamic photoswitches in proteins that impart spatial and temporal control are important to manipulate and study biotic and abiotic processes. Nonetheless, approaches to install these switches into proteins site-specifically are limited. Herein we describe a novel site-specific method to generate photoremovable protein conjugates. Amine-containing chromophores (e.g., venerable  o-nitrobenzyl and less-explored o-nitrophenylethyl groups) were incorporated via transamidation into a glutamine side chain of α-gliadin, LCMV, and TAT peptides, as well as ß-casein and UmuD proteins by transglutaminase (TGase, EC 2.3.2.13). Subsequently, photolysis regenerated the native peptides and proteins. When this modification leads to the reduction or abolishment of certain activities, the process is referred to as caging, as in the case for E. coli polymerase manager protein UmuD. Importantly, this method is simple, robust, and easily adaptable, e.g., all components are commercially available.

Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning.

Image-based spatial transcriptomics methods enable transcriptome-scale gene expression measurements with spatial information but require complex, manually tuned analysis pipelines. We present Polaris, an analysis pipeline for image-based spatial transcriptomics that combines deep-learning models for cell segmentation and spot detection with a probabilistic gene decoder to quantify single-cell gene expression accurately. Polaris offers a unifying, turnkey solution for analyzing spatial transcriptomics data from multiplexed error-robust FISH (MERFISH), sequential fluorescence in situ hybridization (seqFISH), or in situ RNA sequencing (ISS) experiments. Polaris is available through the DeepCell software library (https://github.com/vanvalenlab/deepcell-spots) and https://www.deepcell.org.

Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning.

Image-based spatial transcriptomics methods enable transcriptome-scale gene expression measurements with spatial information but require complex, manually-tuned analysis pipelines. We present Polaris, an analysis pipeline for image-based spatial transcriptomics that combines deep learning models for cell segmentation and spot detection with a probabilistic gene decoder to quantify single-cell gene expression accurately. Polaris offers a unifying, turnkey solution for analyzing spatial transcriptomics data from MERFSIH, seqFISH, or ISS experiments. Polaris is available through the DeepCell software library (https://github.com/vanvalenlab/deepcell-spots) and https://www.deepcell.org.

A Benzarone Derivative Inhibits EYA to Suppress Tumor Growth in SHH Medulloblastoma.

Medulloblastoma is one of the most common malignant brain tumors of children, and 30% of medulloblastomas are driven by gain-of-function genetic lesions in the Sonic Hedgehog (SHH) signaling pathway. EYA1, a haloacid dehalogenase phosphatase and transcription factor, is critical for tumorigenesis and proliferation of SHH medulloblastoma (SHH-MB). Benzarone and benzbromarone have been identified as allosteric inhibitors of EYA proteins. Using benzarone as a point of departure, we developed a panel of 35 derivatives and tested them in SHH-MB. Among these compounds, DS-1-38 functioned as an EYA antagonist and opposed SHH signaling. DS-1-38 inhibited SHH-MB growth in vitro and in vivo, showed excellent brain penetrance, and increased the lifespan of genetically engineered mice predisposed to fatal SHH-MB. These data suggest that EYA inhibitors represent promising therapies for pediatric SHH-MB. SIGNIFICANCE: Development of a benzarone derivative that inhibits EYA1 and impedes the growth of SHH medulloblastoma provides an avenue for improving treatment of this malignant pediatric brain cancer.

High-resolution spatial multi-omics reveals cell-type specific nuclear compartments.

The mammalian nucleus is compartmentalized by diverse subnuclear structures. These subnuclear structures, marked by nuclear bodies and histone modifications, are often cell-type specific and affect gene regulation and 3D genome organization1-3. Understanding nuclear organization requires identifying the molecular constituents of subnuclear structures and mapping their associations with specific genomic loci in individual cells, within complex tissues. Here, we introduce two-layer DNA seqFISH+, which allows simultaneous mapping of 100,049 genomic loci, together with nascent transcriptome for 17,856 genes and a diverse set of immunofluorescently labeled subnuclear structures all in single cells in cell lines and adult mouse cerebellum. Using these multi-omics datasets, we showed that repressive chromatin compartments are more variable by cell type than active compartments. We also discovered a single exception to this rule: an RNA polymerase II (RNAPII)-enriched compartment was associated with long, cell-type specific genes (> 200kb), in a manner distinct from nuclear speckles. Further, our analysis revealed that cell-type specific facultative and constitutive heterochromatin compartments marked by H3K27me3 and H4K20me3 are enriched at specific genes and gene clusters, respectively, and shape radial chromosomal positioning and inter-chromosomal interactions in neurons and glial cells. Together, our results provide a single-cell high-resolution multi-omics view of subnuclear compartments, associated genomic loci, and their impacts on gene regulation, directly within complex tissues.

Exploring Targeted Degradation Strategy for Oncogenic KRASG12C.

KRAS is the most frequently mutated oncogene found in pancreatic, colorectal, and lung cancers. Although it has been challenging to identify targeted therapies for cancers harboring KRAS mutations, KRASG12C can be targeted by small-molecule inhibitors that form covalent bonds with cysteine 12 (C12). Here, we designed a library of C12-directed covalent degrader molecules (PROTACs) and subjected them to a rigorous evaluation process to rapidly identify a lead compound. Our lead degrader successfully engaged CRBN in cells, bound KRASG12Cin vitro, induced CRBN/KRASG12C dimerization, and degraded GFP-KRASG12C in reporter cells in a CRBN-dependent manner. However, it failed to degrade endogenous KRASG12C in pancreatic and lung cancer cells. Our data suggest that inability of the lead degrader to effectively poly-ubiquitinate endogenous KRASG12C underlies the lack of activity. We discuss challenges for achieving targeted KRASG12C degradation and proposed several possible solutions which may lead to efficient degradation of endogenous KRASG12C.