Broad Institute

Vaccinia-related kinase 1 (VRK1) is a promising therapeutic target in gliomas and glioblastomas where VRK2 is silenced by promoter methylation, rendering VRK1 essential for accurate nuclear envelope reassembly following mitosis. Small-molecule ATP-site drug discovery for VRK1 has been hindered by the absence of robust and reproducible biochemical assays. Through virtual screening, we identified previously unreported VRK1-binding scaffolds and validated them in biochemical kinase assays, yielding an 82 nM inhibitor with high selectivity for VRK1 over VRK2. During characterization of this compound, we found that a commonly used commercial time-resolved fluorescence resonance energy transfer VRK1 activity assay is dependent on purification tag-mediated VRK1 dimerization. Leveraging the new inhibitor, we developed fluorogenic tool compounds that increase in fluorescence intensity upon binding to the active site of VRK1 and do not require artificial dimerization of VRK1. The top probe exhibits a Kd of 180 nM and is useful for ligand displacement assays using both fluorescence enhancement and time-resolved fluorescence resonance energy transfer readouts. Together, these results introduce new chemical scaffolds for targeting VRK1, define an assay artifact that has complicated VRK1 inhibitor discovery, and deliver fluorogenic tool compounds for high-throughput screening of ATP-site VRK1 inhibitors, enabling future drug discovery efforts against this emerging cancer vulnerability.

Categorical variants, or sets of genomic alterations constrained by shared properties, are pervasive across clinical, regulatory, and research domains in the biomedical ecosystem, yet their inconsistent and non-computable representation hinders data interoperability and clinical interpretation. We surveyed genomic knowledgebases spanning regulatory approvals and the biomedical literature and found that categorical variants underpin a substantial proportion of clinical genomics knowledge, but are largely described using incompatible bespoke models. To address this, we developed the GA4GH Categorical Variation Representation Specification (Cat-VRS), a constraint-based framework that provides a unified computable representation for both precise and intentionally broad categories across molecular and systemic variant domains. Cat-VRS enables harmonization of genomic knowledgebases, computable category-based search, and automated matching between assayed variants and categorical entities in clinical and research contexts. By providing a principled, extensible model for categorical variation, Cat-VRS enables computable reasoning over genomic variant categories and establishes a foundation for the standardized representation and exchange of genomic knowledge.

Cells can adapt to various environments by changing their biomolecular profiles while maintaining physiological homeostasis. What organizational principles in cells enable the simultaneous realization of adaptability and homeostasis? To address this question, we measure Raman scattering light from Escherichia coli cells under diverse conditions, whose spectral patterns convey their comprehensive molecular composition. We reveal that dimension-reduced Raman spectra can predict condition-dependent proteome profiles. Quantitative analysis of the Raman-proteome correspondence characterizes a low-dimensional hierarchical stoichiometry-conserving proteome structure. The network centrality of each gene in the stoichiometry conservation relations correlates with its essentiality and evolutionary conservation, and these correlations are preserved from bacteria to human cells. Furthermore, stoichiometry-conserving core components obey growth law and ensure homeostasis across conditions, whereas peripheral stoichiometry-conserving components enable adaptation to specific conditions. Mathematical analysis reveals that the stoichiometrically constrained architecture is reflected in major changes in Raman spectral patterns. These results uncover coordination of global stoichiometric balance in cells and demonstrate that vibrational spectroscopy can decipher such biological constraints beyond statistical or machine-learning inference of cellular states.

In response to the comparatively sudden application of industrial scale levels of antibiotics to an ecosystem where naturally produced antibiotics are scarce, namely the ecologies within and around agricultural settings, animal-associated microbes have had to rapidly adapt, mostly relying on mobile genetic elements (MGEs) taken up due to loss of CRISPR functionality. Due to selection for resistance and other adaptive traits carried by dynamic and rapidly recombining MGEs, plasmids and transposons have rapidly accumulated in this human-proximal environment. Because of the occurrence of Enterococcus faecalis in a wide range of hosts up and down the food chain, and the fact that this species represents the greatest generalist of the genus, we comprehensively examined the mobilome of multidrug-resistant E. faecalis (ST330, ST591, ST710, and ST711) from healthy piglets raised on dispersed Brazilian farms, using long-read sequencing, analysis of plasmid pangenomes, and conjugation assays with these strains serving as donors. Genomes ranged from ~2.8-3.1 Mb, with diverse MGEs constituting ~7-15% of those genomes. Large modular antimicrobial resistance-encoding gene blocks (~40 Kb) were observed to be integrated into a ~67 Kb chromosomal segment of the pathogenicity island AF454824. Prophages contributed up to 70% of the chromosomal mobile element content, integrating into both CRISPR-deficient genomes and those with intact type II-A CRISPR1 arrays, which were enriched with Caudoviricetes phage-targeting spacers across all strains. Plasmid content showed pronounced mosaicism driven by diverse insertion sequences, transposons, and related mobile elements, many directly implicated in AMR gene cluster acquisitions. RepA_N, Inc18, and Rep3 plasmids, mostly conjugative, also carried various persistence-related traits, suggesting they may actively enhance agricultural fitness rather than passively accumulate due to loss of CRISPR protection.

Given the global issue of the rising incidence of early-onset colorectal cancer (CRC), we tested the hypothesis that tumor vasculature phenotypes might vary with age at CRC diagnosis. We used in situ multispectral immunofluorescence combined with digital image analysis and machine learning to measure expression of endothelial cell markers [ACKR1 (DARC), CD34, CD36, KDR (VEGFR2), LAMB1 (laminin β1), MADCAM1] and KRT (keratin) in 843 tumors derived from 4476 CRC cases in U.S.-wide prospective cohorts under the prospective cohort incident-tumor biobank method. Overall CD34+ vessel and CD34+LAMB1+ vessel densities inversely correlated with younger age at CRC diagnosis (both Ptrend < 0.0001). In the inverse probability-weighted multivariable-adjusted logistic regression analyses, compared to age ≥70, odds ratios (with 95% confidence interval) for high (vs. low) overall vessel density were 0.85 (0.74-0.99) for age 55-69 and 0.63 (0.48-0.81) for age <55, and those for high (vs. low/negative) CD34+LAMB1+ vessel density were 0.56 (0.47-0.65) for age 55-69 and 0.28 (0.20-0.40) for age <55. Hypovascularities of overall and CD34+LAMB1+ vessels may be microenvironmental characteristics of early-onset CRC if validated by independent studies. Our findings highlight age-related tumor pathobiological differences. Identifying specific biomarkers of early-onset CRC can provide pathogenetic and etiological clues.

Background Chlorogenic acid (CGA) and taurine are well-known antioxidant compounds reported to reduce skin cellular senescence. However, the biological mechanisms underlying their skin-protective effects remain unclear. Methods In this study, we conducted transcriptome-wide RNA sequencing to profile gene expression changes in human epidermal keratinocytes, melanocytes, and fibroblasts following treatment with CGA, taurine, or their combination. To identify aging-related genes, we integrated evidence from aging databases, perceived-age GWAS, enrichment in aging-related gene ontology and pathways, and drug-gene interaction annotations. Validation of representative genes was performed using quantitative real-time PCR. Results A total of 197 differentially expressed genes (DEGs) were identified, of which 62 were prioritized as aging-related DEGs (AR-DEGs) based on their relevance to skin aging anti-senescence-associated pathways, highlighting regulatory transcription factors including TGFB2 , ETS1 , and EGR1 . Co-treatment enhanced the transcriptional effects of CGA and taurine, with several genes exhibiting synergistic responses. Targeted transcriptome-wide association analysis indicated potential links between specific AR-DEGs, such as FST, and phenotypes including perceived age and skin pigmentation. Conclusion By identifying key genes and pathways that contribute to cellular longevity in human skin, this study provides molecular insights for developing anti-aging strategies with potential applications in dermatology.

BackgroundThe integration of multimodal single-cell data enables comprehensive organ reference atlases, yet its impact remains largely unexplored, particularly in complex tissues. Using the kidney as an emblematic example of a complex organ, we perform a systematic evaluation of multimodal single-cell integration strategies, with heart tissue used for additional methodological validation.ResultsWe generate a benchmarking dataset for the renal cortex by integrating 3' and 5' scRNA-seq with joint snRNA-seq and snATAC-seq, profiling 119,744 high-quality nuclei/cells from 19 donors. To align cell identities and enable consistent comparisons, we develop the interpretable machine learning tool scOMM (single-cell Omics Multimodal Mapping) and systematically assess integration strategies. "Horizontal" integration of scRNA and snRNA-seq improves cell-type identification, while "vertical" integration of snRNA-seq and snATAC-seq has an additive effect, enhancing resolution in homogeneous populations and difficult-to-identify states. Global integration is especially effective in identifying adaptive states and rare cell types, including WFDC2-expressing Thick Ascending Limb and Norn cells, previously undetected in kidney atlases.ConclusionsOur work establishes a robust framework for multimodal reference atlas generation, advancing single-cell analysis and extending its applicability to diverse tissues.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13059-026-04002-4.