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Zhang, S.

Publications and source records attributed to Zhang, S..

At least 127 records · Page 7Linked to original sources

TDP-43 regulates chromatin looping and gene transcription through binding and stabilizing DNA G-quadruplex structures

TAR DNA-binding protein 43 (TDP-43) is a multifunctional DNA/RNA-binding protein implicated in transcriptional and post-transcriptional regulation. Dysregulation of TDP-43 is closely correlated with human diseases such as cancer and neurodegenerative diseases. Although its roles in RNA metabolism are well characterized, its function in transcriptional regulation remains largely underexplored. DNA G-quadruplexes (dG4s) are non-canonical nucleic acid structures enriched at gene promoters and regulatory elements, where they facilitate chromatin looping and gene transcription. Here, we investigated the transcriptional regulatory role of TDP-43 by integrating multi-omics datasets, including Hi-C, dG4 ChIP-seq, TDP-43 ChIP-seq, RNA-seq and ATAC-seq from K562 and HepG2 cells. Our analyses demonstrate TDP-43 binding and dG4s formation are highly colocalized at chromatin loop anchors, particularly at promoter and enhancer regions. TDP-43 occupancy at these anchors correlates with increased dG4 stability, chromatin loop interaction frequency, elevated chromatin accessibility, and upregulated gene expression. Morover, TDP-43 knockdown in HepG2 cells revealed a significant reduction in dG4 formation and loop interaction strength, accompanied by widespread transcriptional dysregulation. Collectively, our findings highlight a novel regulatory role of TDP-43 in facilitating long-range chromatin interactions and transcriptional activation through binding to and stabilizing dG4 structures, providing a mechanistic basis for gene dysregulation driven by TDP-43 dysfunction in diseases.

bioinformatics↗

BiomniBench: Process-level Evaluation of LLM Agents for Real-world Biomedical Research

LLM agents now perform real biomedical research, but evaluating them rigorously is hard. Outcome-only benchmarks fail in two ways. First, a correct final answer can come from memorization, reward hacking, or wrong reasoning that produces the right number by chance. Second, valid alternative analyses are marked wrong simply because they differ from the reference. We introduce BiomniBench, a process-level evaluation framework that scores the full agent trajectory against expert-designed, task-specific rubrics. Our first release, BiomniBench-DA, contains 100 data-analysis tasks across 17 task types, 5 disease areas, and a general-biology category, each based on a paper from journals such as Nature, Cell, and Science and co-developed with an original author or a domain expert. Benchmarking frontier and open-weight models across four agent harnesses reveals three findings. Frontier and open-weight bases cluster within a few points of each other, with substantial headroom for all models. The agent harness shifts scores by more than the gap between successive model generations. Agents reliably ground claims in real sources yet consistently fall short on method selection, biological interpretation, and scientific reasoning. BiomniBench is the first process-level benchmark for LLM agents in biomedical research, providing the dimension-level diagnostics that outcome scoring cannot. Datasethuggingface.co/datasets/phylobio/BiomniBench-DA

bioinformatics↗

PTM-dCN: Latent Space Control for Post-translational Modification-aware Protein Design

AO_SCPLOWBSTRACTC_SCPLOWPost-translational modifications (PTMs) are critical for protein function, yet their precise design by harnessing site specific information derived from native proteins remains challenging. Here, we present a deep learning-based PTM design framework that integrates latent diffusion models with ControlNet for sequence generation with site-specific PTM-control. The framework incorporates a PTM-aware protein language model featuring extractor, trained on a curated SwissProt PTM dataset with specialized modification tokens. Through de novo generation of protein sequences with designated PTM sites, our framework facilitates the exploration of PTM-driven functional landscapes and advances position-aware protein engineering.

bioinformatics↗

NFIC-mediated CaSR endocytosis defines a hyperactive TOMM20highCHGAhigh oxyphil cell state as a pathological driver of autonomous secondary hyperparathyroidism

Secondary hyperparathyroidism (SHPT) is a debilitating complication of chronic kidney disease. Its clinical management is frequently compromised by calcimimetic resistance, a refractory state primarily driven by the progressive downregulation of the membrane calcium-sensing receptor (CaSR). Despite the centrality of CaSR as a therapeutic target, the mechanisms governing its aberrant expression and membrane localization remain incompletely elucidated. Here, we generated a single-cell transcriptomic atlas of human parathyroid tissues from SHPT and primary hyperparathyroidism (PHPT) patients, uncovering a unique stromal-immune niche that is specifically induced by uremic stress in SHPT. Our data also observed a striking dissociation between CaSR mRNA and its abundance as a membrane protein in SHPT tissues. Pseudotime trajectory analysis showed a progressive decline in CaSR pathway activity and a concomitant increase in endo-lysosomal activity along the trajectory, terminating in pathological oxyphil cells as the endpoint of chief cell differentiation in SHPT. Mechanistically, Nuclear Factor I C (NFIC) transcriptionally activated clathrin light chain B (CLTB) and Ras-related protein Rab7a (RAB7A) to trigger clathrin-mediated endocytosis and lysosomal degradation of CaSR, thus reducing its membrane abundance. This degradative program was further validated by multiplex immunofluorescence in TOMM20highCHGAhigh pathological oxyphil cells in human SHPT tissues. To translate these mechanistic findings into a clinically actionable strategy, we repurposed the clinically approved lysosomal inhibitor hydroxychloroquine (HCQ) to block this CaSR degradation pathway. In patient-derived xenograft (PDX) mouse models, co-administration of HCQ and cinacalcet acted synergistically to restore membrane CaSR expression, normalize serum PTH and calcium levels and suppress parathyroid tumor growth more effectively than monotherapies. Collectively, our single-cell-guided study identifies an NFIC-driven endo-lysosomal program as a previously unrecognized mechanism underlying CaSR downregulation and calcimimetic resistance in SHPT, and establishes HCQ repurposing as a clinically tractable therapeutic strategy for patients with refractory SHPT.

cell biology↗

The turn less taken: Investigating patterns in β-turn dynamics using large-scale molecular dynamics data

{beta}-turns are among the most common structural motifs in proteins, yet their conformational dynamics and sequence determinants remain incompletely understood. Here we present a data-driven classification and dynamic analysis of {beta}-turn conformations using large-scale molecular dynamics trajectories from the mdCATH database. Clustering of backbone dihedral angles using a cross-bond Ramachandran representation identifies six {beta}-turn types, including a previously uncharacterized hybrid I/I' cluster that combines geometric features of canonical type I and I' conformations. Time-resolved analysis indicates that this hybrid state acts as a transient intermediate state of {beta}-turns. Transitions observed in molecular dynamics simulations closely match NMR ensembles and altlocs detected in X-ray crystal structures, with the most dominant exchanges occurring between type I and II, and between type I' and II' turns. Sequence analysis shows that each turn type exhibits characteristic amino acid preferences at the central residues (i + 1 and i + 2). Within these overall preferences, specific residue pairs display distinct biases toward static or dynamic behavior. Targeted in silico substitutions that interchange dynamic- and static-enriched residue pairs shift the conformational behavior of turns accordingly, providing direct support for these sequence-dynamics relationships. Analysis of flanking secondary-structure environments reveals that structural context further modulates turn flexibility, with strand- and coil-associated turns exhibiting higher dynamic propensity than helix-associated turns. Together, these results reveal how sequence composition and structural context jointly shape the conformational landscape of {beta}-turns.

biochemistry↗

Parallel Activation and Interference CRISPR (PAIR) with Sequencing Uncovers DNA Repair Networks Guiding Precision Cell Engineering

The dynamic balance of cellular homeostasis is often maintained by opposing regulatory pathways, yet most genetic screens interrogate them in one direction and therefore miss the bidirectional gene-gene interactions that shape complex phenotypes such as DNA damage response (DDR). Here, we present PAIR (Parallel Activation and Interference CRISPR), a bidirectional perturbation platform that enables simultaneous activation and suppression of distinct genes within the same cell using CRISPR activation (CRISPRa) and Cas13d RNA knockdown. Applying PAIR to the CRISPR/Cas9 induced DSB repair screen, we mapped gene-gene interactions across competing repair branches and identify synergistic perturbations, including NBN activation combined with suppression of end-joining factors, that shift repair outcomes toward homology-directed repair (HDR) and improve the precision of CRISPR-based gene editing. Using coupled PAIR with single-cell transcriptomic, we further demonstrated that NBN activation induces inflammatory and interferon programs, whereas co-suppression of end-joining factors buffers this response, revealing transcriptional states missed by conventional unidirectional perturbations. To translate these findings into non-viral chimeric antigen receptor (CAR) T cell engineering, we developed an mRNA-based strategy for parallel overexpression and knockdown of NBN-anchored DDR effectors in primary T cells, priming the T cells into a transient HDR-favored state that enhances the efficiency of CAR knock-in on the TRAC locus. Together, the PAIR system provides a general framework for studying opposing regulatory networks, uncovering hidden cell states, and guiding cell-state engineering through bidirectional perturbation.

bioengineering↗

A Scalable Sign-Aware Multi-Omics Knowledge Graph Foundation Model for Mechanistic Drug Action and Clinical Response Predictions

Mechanistically predicting drug action requires distinguishing activating from inhibitory interactions across broad chemical space, yet most biomedical knowledge graphs and graph neural networks (GNNs) rely on unsigned associations that obscure regulatory logic and have a limited chemical coverage. Here we present SIGMA-KG (SIGned Multi-omics Atlas Knowledge Graph) and FLASH (Fast Lightweight Architecture for Signed Heterogeneous GNN), a graph foundation model pretrained through self-supervised learning on SIGMA-KG. SIGMA-KG integrates chemogenomic perturbation, transcriptomic, proteomic, and clinical data while explicitly encoding biological polarity and directionality. FLASH preserves polarity composition across multi-hop pathways through structural balance principles, enabling scalable mechanistic reasoning. Without task-specific fine-tuning, FLASH consistently outperforms or matches nine state-of-the-art unsigned, relational, and signed graph baselines across drug mode-of-action prediction, clinical response modeling, and drug-drug interaction prediction, while substantially improving computational efficiency. FLASH further enables explainable inductive drug repurposing, achieving a 69.6% external clinical validation success rate across four complex diseases.

systems biology↗

Distinct HPO axis responses and ovarian aging trajectories to chronic unpredictable mild stress in reproductively young versus middle-aged female mice

Psychosocial stressors are key contributors to ovarian functional decline. Chronic unpredictable mild stress (CUMS) is widely used to model stress-induced premature ovarian insufficiency (POI) in mice; however, current animal models do not adequately reflect middle-aged women, who represent a key population exposed to chronic psychosocial stress, nor do they capture the dynamic progression toward POI. Here, female C57BL/6 mice aged 2 or 6 months were subjected to CUMS for 8 or 12 weeks. Estrous cyclicity, endocrine profiles, ovarian histology, and transcriptomic changes in HPO axis-related tissues were systematically analyzed. After 8 weeks of exposure, 2-month-old mice exhibited impaired pituitary responsiveness to estradiol negative feedback, as evidenced by dysregulated FSH secretion, indicating reduced stress tolerance compared with 6-month-old mice. Following 12 weeks of CUMS exposure, both age groups showed significant reductions in ovarian size and follicle numbers across all developmental stages. These findings demonstrate that CUMS induces an age-dependent progression toward POI, with short-term exposure eliciting compensatory phases preceding overt ovarian insufficiency, accompanied by distinct endocrine and reproductive alterations and differential responsiveness of the HPO axis. Transcriptomic analyses revealed age-dependent stress responses: ovaries of 2-month-old mice displayed marked activation of inflammatory and immune-related pathways, whereas 6-month-old mice showed sustained upregulation of protein kinase-related signaling networks. Notably, the 6-month-old CUMS model more closely recapitulates stress-associated reproductive aging in adult women. In briefCUMS has been widely used to establish mouse models of psychosocial stress-induced POI. However, current animal models do not adequately reflect middle-aged women, who represent a key population exposed to chronic psychosocial stress, nor do they capture the dynamic progression toward premature ovarian insufficiency (POI). In this study, we demonstrate that different durations of CUMS exposure induce distinct stages of ovarian dysfunction in both young and middle-aged mice, with short-term exposure driving age-dependent compensatory phases and prolonged exposure leading to overt POI, both accompanied by divergent endocrine and reproductive alterations, alongside age-dependent changes in HPO axis responsiveness to CUMS. Notably, the 6-month-old CUMS model shows greater clinical relevance in recapitulating chronic psychosocial stress and stress-related reproductive aging in adult women.

physiology↗

Coenzyme A is a redox sensing cofactor for malic enzyme 2 regulating oxidative stress and mitochondrial metabolism

Coenzyme A (CoA) is an essential cofactor required for numerous metabolic reactions, yet its ability to bind and regulate proteins remains poorly defined. Using a proteomic approach, we identified malic enzyme 2 (ME2) as a CoA-binding protein. ME2 uses NAD(P)+ to convert malate to pyruvate, generating NAD(P)H to support energy production and redox homeostasis. ME2 binds CoA at an allosteric site previously thought to bind NAD(P)+. Reduced CoA has minimal effect on ME2 activity, but the oxidized form, CoA disulfide, strongly activates ME2 by promoting ME2 tetramerization and a catalytically efficient closed conformation. Under oxidative stress, ME2 facilitates CoA disulfide formation, enhancing NADPH production and cellular defense against reactive oxygen species (ROS). Mice with ME2 mutation that cannot bind CoA show impaired muscle performance, elevated ROS, and mitochondrial dysfunction. These findings establish CoA as a redox-sensing cofactor, allowing cells to respond to ROS and promote mitochondrial metabolism, and expanding the function of this essential cofactor.

biochemistry↗

Eggerthella lenta evades bacteriophage through reversible megabase-scale inversions of capsular polysaccharide gene clusters

Bacteriophages are a promising tool for microbiome editing, yet their development has been constrained by limited insights into bacteriophage-host interactions within their shared mammalian body habitat. We isolated a lytic phage {Phi}KL11 that efficiently targets a disease-associated member of the human gut microbiota, Eggerthella lenta, during in vitro growth. However, {Phi}KL11 selects for a pre-existing and reversible bacteriophage-resistant sub-population in mice. Long-read sequencing revealed a massive genomic inversion event, representing >50% of the E. lenta genome, enriched in response to bacteriophage infection. Transcriptomics linked this inversion to the altered expression of three capsular polysaccharide synthesis (CPS) gene clusters and transmission electron microscopy confirmed differential capsule production. Finally, we show that {Phi}KL11 has a broad host range attributable to CPS and other strain-variable genes. These findings suggest a previously unrecognized strategy for phage evasion in the gut, involving megabase-scale genomic inversions and reversible capsule variation driving phage resistance.

microbiology↗

Blood Based Biomarkers of DNA Methylation Associated with Platinum Resistance in High Grade Serous Ovarian Cancer

BackgroundHigh grade serous ovarian cancer (HGSC) is initially a responsive tumor to platinum (Pt)-based therapy. Pt resistance in HGSC is associated with epigenetic modifications and hypomethylating agents (HMAs) have been studied as carboplatin resensitizing agents. As DNA methylation is detectable in cancer cells and in blood, here we aimed to develop a blood-based methylation signature associated with cancer and cancer recurrence in HGSC. ResultsWe evaluated genome-wide DNA methylation in de-identified peripheral blood mononuclear cells (PBMCs) from women 1) without cancer (controls, n=20); 2) newly diagnosed HGSC (prior to treatment, Pt-naive, n=60) 3) Pt-resistant recurrent HGSC before and after treatment with the novel HMA/DNA methyltransferase inhibitor (DNMTI) guadecitabine (Pt-resistant, n=30). The Pt-resistant patients were enrolled in NCT02901899 clinical trial testing guadecitabine and the PD-1 inhibitor pembrolizumab. DNA extracted from PBMCs was analyzed by using Infinium MethylationEPIC BeadChips. There were 30,369 differentially methylated loci (DMLs) in Pt-naive patients vs. controls (adj. p < 0.05, {beta} >10%), with most loci being demethylated. Enriched pathways in PBMCs from cancer patients included mechanisms of cancer, neutrophil degranulation, and cancer-related signaling pathways (PI3K/AKT, STAT3, HGF, interleukins). The number of DMLs was greater (880 DMLs; adj. p<0.05, {beta}>10%) in Pt-resistant vs. Pt-naive patients, and top enriched pathways associated with Pt-resistant HGSC included pathways in cancer, metabolic pathways, platelet activation, ABC transporters and signaling pathways (calcium, PI3K/AKT, MAPK, Ras, ErbB, Hippo, Wnt). Massive genomewide hypomethylation 5 days after treatment with guadecitabine was observed (13,742 DMLs; adj. p<0.05, {beta}>10%), which persisted 30 days after discontinuation of treatment. Pathways enriched by hypomethylated genes in PBMCs following guadecitabine treatment interestingly included pathways related to neuronal signaling, such as glutaminergic receptor signaling, axonal guidance signaling, synaptic long-term depression, synaptogenesis signaling and serotonin receptor signaling. Deconvolution analysis of the methylome data of PBMCs from Pt-resistant recurrent HGSC before versus after HMA treatment predicted increased naive B cells, memory and naive CD+ T cells, naive CD4+ T cells, and neutrophils and decreased monocytes. ConclusionsWe propose new DMLs associated with Pt-naive versus Pt-resistant HGSC. These findings can lead to new biomarkers for HGSC.

genomics↗

Single cell eQTL mapping reveals convergent glial-neuronal risk architecture in Parkinson's disease

Synucleinopathies affect [~]15 million people and are classically divided into neuronal (Parkinsons disease (PD), dementia with Lewy bodies) and glial (multiple system atrophy) disorders. Here we challenge this dichotomy. We functionally fine-map 90 PD GWAS signals across nine cell types in cortex and substantia nigra using disease-context, population-scale single-nucleus eQTL meta-analysis (N = 1,197), bulk brain eQTL analysis (N = 1,182), and Mendelian randomization. A stringent causal framework integrates single-nucleus allelic imbalance (snASE) with orthogonal validation. We identify 125 functional risk genes for 50 loci--nearly doubling supported genes--and assign genes and cell types to over half of GWAS signals. Unexpectedly, 51% of risk genes are regulated in glia, particularly oligodendrocytes and their precursors. Across cell types, risk converges on a shared glial-neuronal vesiculopathy network. These findings uncover a convergent glial-neuronal risk architecture and establish a single-cell atlas for context-aware gene discovery and precision therapeutics for PD.

genetics↗

OneGenomeRice (OGR): A Genomic Foundation Model for Rice

The transition of genomics to a predictive intelligence discipline is driven by the advent of genomic foundation models. While substantial progress has been observed in all-life and human-centric models, plant species, particularly for the staple crops, remains hindered by a lack of models. Here we introduce OneGenome-Rice (OGR), a rice (Oryza sativa) genomic foundation model pre-trained on a genomic dataset comprising 422 high-quality genomes of cultivated and wild rice. OGR is engineered upon a Mixture of Experts (MoE) transformer architecture with 1.25-billion parameters and supports an ultra-long context window of up to 1 million base (Mb) pairs at single-nucleotide resolution. A comprehensive benchmark demonstrated that OGR significantly outperforms existing state-of-the-art multi-plant or all-life genome models in 11 categories (e.g. motif identification, sweep detection, etc). We further demonstrated the utility of OGR in several downstream applications, such as indica-japonica subspecies introgression analysis, identification of agronomy trait-associated functional loci and prediction of gene expression from DNA sequences. These results establish OGR as a promising foundational computational infrastructure for rice functional genomics and precision breeding. The OGR and its fine-tuned models, including pretrained weights, training code and the rice genomic benchmark suit, have been fully opened.

genomics↗

Benchmarking Generative Large Language Models for de novo Antibody Design and Agentic Evaluation

Despite major advances in computational antibody engineering, no systematic comparison of modern open-source LLM backbone families for antibody sequence generation exists, nor is it known whether architectural differences matter at compact model scales. In this study, five compact transformer variants inspired by prominent open-source LLM families (Llama-4, Gemma-3, DeepSeek-V3, Mistral 7B, and NVIDIA Nemotron-3) were customized and trained from scratch for de novo VH single-domain antibody (sdAb) design. All five models were pretrained from scratch on 15 million sequences from the Observed Antibody Space (OAS) database. Pretraining yielded uniformly high generative fidelity across architectures: sequence diversity 0.507-0.516 (CV=0.8%), uniqueness approaching 1.0, and novelty 0.925-0.977 (CV=2.2%). The models were subsequently fine-tuned on disease-stratified repertoires spanning SARS-CoV-2 (n=4,688), HIV (n=430), HER2 (n=22,778), and Ebola virus (n=2,868). Structural assessment of top-ranked candidates of those case studies via AlphaFold-2, Boltz-2, RoseTTAFold-2, and ESMFold produced mean pLDDT scores of 92.88{+/-}1.54 to 93.77{+/-}2.16, with no statistically significant inter-model differences (Kruskal-Wallis H=2.06, p>0.05; N=100), indicating no statistically detectable difference was observed across architectures at this compressed scale in a single-seed experiment, suggesting that generative capacity at this parameter regime is primarily determined by training data and model scale rather than family-specific design elements at this scale. Computational docking yielded predicted binding free energies of -36.34 to -65.60 kcal/mol; independent biological rigor validation through IMGT-defined CDR-H3 extraction, BLASTp novelty assessment, and NetMHCIIpan 4.3 MHC-II immunogenicity profiling collectively confirmed antigen-binding loop novelty (CDR-H3 identity 0-29% to closest database hits), germline-consistent humanness (77-90% VH germline content), and immunogenically silent antigen-binding surfaces with no strong MHC-II binders detected across CDR regions in any candidate. We further introduce a proof-of-concept agentic evaluation pipeline leveraging the Model Context Protocol (MCP) with Claude Sonnet 4.6, enabling automated structural profiling and candidate prioritization across disease targets.

bioinformatics↗

Deep mapping of structural perturbations to energetics enables precise TCR design

Affinity optimization and cross-reactivity profiling are pivotal for T-cell receptor (TCR) engineering and immunotherapy, yet remain hindered by the vast diversity of the TCR repertoire and limited structural insights. Here, we present mpTCRai, a deep learning framework that captures the sequential characteristics of antigen presentation and recognition with high precision. Leveraging these precise structural predictions, we established a contact hotspot-based scoring mechanism that explicitly maps structural perturbations to energetic changes, yielding a strong correlation with experimental affinity (r = -0.88). In application, the model identified critical molecular switches, such as specific G-to-A substitutions, and revealed their dependence on structural context. Furthermore, it effectively distinguished functional variants from dangerous cross-reactive mutations like Y5W, thereby mitigating the risk of off-target toxicity. Guided by these insights, we computationally designed four novel A6-TCR variants, demonstrating a rational strategy for candidate selection in adult T-cell leukemia. This work establishes a unified platform integrating structural and energetic constraints to advance precise, safe TCR therapeutic design.

immunology↗

Droplet-compatible single-cell DNA methylation sequencing with PreTIC

Single-cell DNA methylation sequencing has remained technically specialized due to challenges of interfacing conversion chemistry with droplet microfluidics. We introduce pre-tagmentation in situ conversion (PreTIC), which enables whole-methylome profiling on a commercial droplet platform using off-the-shelf reagents. With PreTIC, we produce over 13,000 single-cell methylomes from fixed frozen cells in two days and resolve cell-specific epigenetic variation in human peripheral blood mononuclear cells.

genomics↗

Combination of engineered cell type-specific promoters and a high-efficiency AAV capsid restores hearing in adult DFNB1 mice model with demonstrated safety in nonhuman primate

A major challenge in gene therapy for GJB2-related hearing loss (DFNB1)--the most common form of hereditary deafness--is achieving efficient and precise connexin 26 delivery. Herein, we engineered two cell type-specific promoters (GJB2-1 and WFS1-2274) and developed an AAV capsid, AAV-MAS012, with enhanced transduction efficiency in mature cochlear cells. Our AAV-mediated gene therapy systems restored hearing of low-to-mid-frequencies in newborn Gjb2 cKO mice to wild-type levels and maintained for 45 weeks. Additionally, our therapeutic systems restored low-to-mid-frequencies hearing function to wild-type levels in adult Gjb2 cKO mice. A humanized version of the therapy, AAV-MAS012-WFS1-2274-hGJB2, rescued hearing function in two distinct Gjb2-deficient mouse models, and demonstrated a favorable safety profile in nonhuman primates. This study represents the first successful hearing restoration in adult Gjb2-deficient mice. The significant therapeutic efficacy of the humanized gene therapy system shows great potential for clinical translation in DFNB1 patients.

genetics↗

Chromatin association promotes UBR5-mediated degradation of Rb

The retinoblastoma protein Rb is a cell cycle inhibitor that plays a central role in regulating the G1/S cell cycle transition. Un-/hypo-phosphorylated Rb suppresses E2F transcription activity by binding to E2F/DP dimers and recruiting chromatin remodelers to prevent cells from entering S phase. For cells to progress through the G1/S transition, Rb is inactivated by two mechanisms: the "classic" pathway of Rb hyperphosphorylation by Cyclin-CDK complexes, and a recently identified "degradation" mechanism driven by the E3 ubiquitin ligase UBR5. These two pathways are interconnected, as only the un-/hypo-phosphorylated Rb can be degraded, and the hyper-phosphorylated Rb is stabilized to promote its reaccumulation in preparation for the next cell division cycle. However, the molecular basis for how Rb is stabilized upon phosphorylation remains unclear. In this study, we found that UBR5 preferentially targets chromatin-associated proteins for degradation. Since Rbs chromatin association is modulated by its phosphorylation, we hypothesized that phosphorylation may affect Rb stability by altering its chromatin association. To test this, we constructed a series of un-phosphorylatable Rb variants with graded reductions in chromatin association. Consistent with our hypothesis, we observed a strong correlation between an Rb variants chromatin association and its half-life. Fusing these Rb variants to histone H1 increased chromatin association to similar levels and equalized their protein half-lives. Taken together, these findings show how phosphorylation stabilizes Rb by promoting its dissociation from chromatin. This provides a striking example for how sub-organellar protein localization may be used to regulate stability.

molecular biology↗