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Biology subjects

Shen, R.

Publications and source records attributed to Shen, R..

At least 19 recordsLinked to original sources

The bHLH121-CAT2 module maintains root tip redox homeostasis to confer salt tolerance additively with the SOS pathway in Arabidopsis

Soil salinity inhibits plant growth, in part, by restricting the availability of essential mineral nutrients such as iron (Fe). Although Fe deficiency frequently coincides with salt stress in the field, the molecular mechanisms integrating Fe homeostasis with salt tolerance remain largely unknown. Here, we identify the Fe deficiency response regulator bHLH121 as a key coordinator of salt tolerance in Arabidopsis. Loss-of-function mutants of bHLH121 exhibit pronounced hypersensitivity to salt stress, with severely impaired primary root elongation and reduced seedling biomass. Transcriptomic and histochemical analyses reveal that bHLH121 is required to maintain reactive oxygen species (ROS) homeostasis specifically in root tips under salt stress. We further demonstrate that CATALASE 2 (CAT2) is a direct downstream target of bHLH121, and that CAT2 overexpression fully rescues the salt hypersensitivity of the bhlh121 mutant. Importantly, this bHLH121-CAT2 module operates independently of the classical SOS pathway, as sos2 bhlh121 double mutants display additive salt sensitivity. Together, our findings uncover a novel regulatory module in which bHLH121 governs root tip redox homeostasis through CAT2 to confer salt tolerance, providing a direct mechanistic link between the Fe regulatory network and abiotic stress resilience in plants.

plant biology↗

The conserved function of bHLH121 and overexpression of N-terminal bHLH121 fragment suppresses iron deficiency response in Arabidopsis

Iron (Fe) homeostasis is fundamental to plant growth and development and is centrally regulated by a well-conserved network of basic helix-loop-helix (bHLH) transcription factors. In Arabidopsis thaliana, bHLH121 regulates the expression of FER-like iron deficiency-induced transcription factor (FIT) and clade Ib bHLH38/39/100/101 genes, among others. However, its functional conservation remains unexplored, and some contradictory results have been reported regarding the effects of bHLH121 overexpression. Here, we investigated the evolutionary conservation of bHLH121 through complementary tests in the Arabidopsis bhlh121 mutant created by CRISPR/Cas9 gene editing. We also investigated the effects of ectopically expressing full-length, N-terminal, and C-terminal fragments of bHLH121 on plant responses to Fe deficiency in Arabidopsis. Transgenic plants overexpressing the full-length bHLH121 driven by the cauliflower mosaic virus 35S promoter (bHLH121 ox) resulted in shorter roots and more severe leaf chlorosis compared to wild-type plants under Fe limiting conditions. Moreover, overexpression of the N-terminal fragment (N121 ox) rendered plants highly sensitive to Fe deficiency, whereas overexpression of the C terminal fragment (C121 ox) did not. Consistent with the phenotypic observations, N121 ox plants accumulated lower Fe content, and the ferric chelate reductase activity was significantly reduced. In N121 ox plants, the induction of key Fe regulatory genes, especially FIT, was significantly inhibited under Fe deficiency. Confocal imaging showed that both N121-GFP and C121-GFP fusion proteins could localize to the nucleus. Electrophoretic mobility shift assay showed that both full-length bHLH121 and N121 could effectively bind the probes derived from the promoter of FIT. The present work reveals a conserved function of bHLH121 in Fe homeostasis across several dicot species and demonstrates that the N121 may possess a dominant nature in Fe deficiency responses.

plant biology↗

TRAPPC8 Is an Endogenous Brake on UFMylation That Suppresses Tauopathy

UFMylation, a ubiquitin-like protein modification, drives tau spread through the brain, but what keeps this process in check has remained unclear. We show that TRAPPC8 acts as a natural brake on UFMylation, binding directly to the E1 enzyme UBA5 to dampen pathway activity. In Alzheimer's disease brain tissue, TRAPPC8 is reduced while UFMylation is elevated, suggesting this brake fails as disease progresses. Sustaining UFMylation in human iPSC-derived neurons increased tau aggregation and spread while disrupting lysosomal function and lipid balance. Restoring TRAPPC8-UBA5 binding reversed these defects through the lysosomal protein CLN8, which restored lysosomal function and reduced tau pathology. Notably, expressing just the UBA5-binding region of TRAPPC8 was enough to suppress tau pathology in vivo, marking it as a promising therapeutic target.

neuroscience↗

Spinal injury induces a stem cell-like progenitor state that promotes regenerative neurogenesis via clcf1 in zebrafish.

After spinal injury, zebrafish, in contrast to mammals, show regenerative neurogenesis, characterized by enhanced injury-induced proliferation of ependymo-radial glial cells (ERGs) and an increase in injury-induced generation of neurons from these progenitors. It is unclear whether regenerative neurogenesis simply recapitulates development or uses regeneration-specific mechanisms. Using scRNA-seq and in vivo validation we find a spinal injury-induced state in ERGs (iiERGs) in larval zebrafish. This cell state emerges mostly without proliferation and has stem cell characteristics, including weak expression of neurogenic genes and strong expression of stemness factors, such as lin28a. Expression of lin28a is not detectable during ongoing developmental neurogenesis. Following spinal cord lesion, lin28a disruption increases the numbers of ERGs undergoing neuronal differentiation and of newly-generated neurons, at the expense of proliferating ERGs and iiERGs. This supports a stemness-preserving role of lin28a in iiERGs. Importantly, iiERGs secrete growth factors, including the regeneration-specific cytokine clcf1, which depends in part on lin28a expression. Disruption of clcf1 signalling impairs spinal progenitor proliferation and injury-induced generation of new neurons, but does not affect the emergence of iiERGs. Over-expression of clcf1 is sufficient to augment neurogenesis in unlesioned animals without inducing the iiERG state, indicating that clcf1 acts as a generic growth factor. Hence, we describe an injury-specific stem cell-like ERG population that regulates regenerative neurogenesis by attenuating neuronal differentiation via lin28a and promoting progenitor proliferation via clcf1.

neuroscience↗

Metabolic dehalogenation of halomethanes by mercury methylators

Mercury (Hg) methylators play key roles in the global Hg cycle. Nonetheless, the Hg methylators are widely present in Hg-absent environments and the Hg methylation is a cometabolic process without cell growth, which leave the origin and evolution of the Hg methylation as a mystery. Here, we reported the CCl4/trihalomethane-to-dihalomethane dehalogenation by model Hg methylators in a metabolic way. Heterologously-expressed HgcAB catalyzed both the CCl4 dechlorination and Hg methylation. Halomethanes were shown to sustain the Hg-methylation community without adding external carbon source, electron donor and acceptor. Metadata analyses suggested the halomethane dehalogenation potential of Hg methylators at the global scale. These results, together with much higher global flux and kinetic Vmax of the metabolic halomethanes dehalogenation relative to the co-metabolic Hg methylation, suggested halomethanes as the potential HgcAB substrates for the evolution of Hg methylation.

microbiology↗

A scalable approach to resolving variants of uncertain significance

Over 90% of missense variants across [~]4,000 disease-associated genes are variants of uncertain significance (VUS). Experimental variant effect measurements provide critical evidence about pathogenicity and inform disease biology, but most variants lack data and clinical translation has been limited. The Impact of Genomic Variation on Function Consortium generated experimental data for 62,215 variants across ten genes using multiplexed assays and 1,407 variants across 163 genes using arrayed assays, curated 193,139 additional community-generated variant effect measurements across 30 additional genes, and developed automated calibration methods for translating experimental data and variant effect predictions into clinical evidence. To reduce current VUS, we developed a scalable workflow using only experimental and predictive evidence, enabling reclassification of 75% of the 16,115 VUS in these genes as pathogenic or benign with <1% error. To minimize future VUS, we analyzed >90,000 unobserved variants; 62% had enough evidence to be "preclassified" as pathogenic or benign. We validated our data, evidence and classifications using All of Us and created interactive resources to enable clinical use of the calibrated data. Thus, for 40 genes, representing 1% of the clinical genome, we resolve most existing VUS and future variants, illustrating how systematic use of scalable evidence can empower genomic medicine.

genomics↗

Chromatin architecture and physical constriction cooperate in phenotype switching and cancer cell dissemination

Phenotypic plasticity is a prominent cancer feature that contributes to metastatic potential and resistance to therapy across multiple cancer types. Cancer cell state transitions have been attributed to transcriptional programs, such as the AP1/TEAD-regulated gene network driving the mesenchymal-like (MES) phenotype. In addition, during dissemination, tumor cells are subjected to variable loads of physical mechanical pressure and constriction across transited tissue, which are thought to impact nuclear molecular crowding. How the interplay between mechanical pressure, global 3D nuclear architecture and transcriptional programs contributes to MES identity and metastatic adaptation remains unclear. Using cutaneous melanoma as a model for early dissemination, we integrate in vitro and in vivo epigenomic profiling with nanoscale imaging of cell lines and patient samples to investigate chromatin organization features underlying the MES phenotype. We find that in MES cells, CTCF is relocated from domain boundaries to regulatory regions of EMT-like genes, leading to reduced insulation, extended topological associated domains (TADs) and increased inter-domain contacts, and de novo formation of chromatin hubs. This conformational rewiring, along with loss of heterochromatin, supports nuclear deformability during invasion and dissemination. Conversely, physical constriction of melanocytic cells induces MES-like chromatin features--including CTCF repositioning and heterochromatin loss-- and promotes metastasis in vivo. Similarly, pharmacological inhibition of the heterochromatin mark H3K9me3 triggers MES characteristics and increases invasiveness. These results demonstrate that metastatic competency involves both epigenetic and structural nuclear reprogramming, enabling shifts in gene networks and physical adaptability. Our findings reveal mechanistic links between nuclear architecture and aggressive tumor behavior, identifying potential biomarkers and therapeutic targets to intercept metastatic progression.

cancer biology↗

Characterization and application of hyperthermia-evoked seizures in a mouse model of focal cortical dysplasia

Rodent models of drug-resistant epilepsy are widely used to uncover mechanisms of seizures and to test the efficacy of treatments; however, the stochastic and relatively infrequent nature of spontaneous seizures in these models makes it challenging to observe and manipulate peri-ictal activity, and to rapidly screen therapeutics. As fever has been identified as a clinical seizure trigger, we investigated the ability of induced hyperthermia to trigger seizures in a mouse model of focal cortical dysplasia (FCD), a common cause of drug-resistant epilepsy. Experimental mice were generated via in utero electroporation of a gain-of-function RHEB variant (RHEBp.P37L). In adult Rheb-FCD mice, hyperthermia elicited behavioral seizures [~]80% of the time, with a mean temperature threshold of [~]40 {degrees}C. Using this acute paradigm, as a proof-of-concept, we found that chemogenetic inhibition of a subset of excitatory neurons within the dysplasia significantly elevated the threshold for hyperthermia-evoked seizures. We then confirmed the relevance of this acute finding to spontaneous epileptiform activity, using repeated chemogenetic inhibition across chronic recordings to confirm a reduction of spontaneous seizures as well as interictal spikes. Overall, our data demonstrate that hyperthermia-evoked seizures can be readily elicited in Rheb-FCD mice, offering a tractable platform for evaluating therapeutic interventions targeting seizure susceptibility in focal epilepsy.

neuroscience↗

Inhibition of CGRP receptor ameliorates AD pathology by reprogramming lipid metabolism through HDAC11/LXRβ/ABCA1 signaling

The Calcitonin gene-related peptide (CGRP) receptor has gained attention in Alzheimers Disease (AD) research due to its involvement in regulating neuroinflammation. However, its role and mechanism in AD pathology remain unclear. Here, we demonstrate that CALCRL, a core component of the CGRP receptor, is upregulated in the hippocampus of AD dementia patients and 5xFAD mice. Knockout of the CGRP receptor ligand Calca or pharmacological blockade using Rimegepant (Rim), reduces soluble A{beta}1-42 oligomer-induced neuronal death and glial inflammation. Rim treatment also rescues neurobehavioral impairments, neurodegeneration, and lipid metabolism dysfunction in 5xFAD mice. Mechanistically, these effects are mediated through HDAC11 inhibition, which enhances LXR{beta} acetylation and ABCA1 expression, promoting the reprogramming of neuronal lipid metabolism. Importantly, this CALCRL/HDAC11/LXR{beta}/ABCA1 axis is conserved across both humans and mice. Our findings uncover a novel mechanism underlying AD pathogenesis and highlight the therapeutic potential of targeting CGRP signaling in AD. HIGHLIGHTSInhibition of CGRP receptor ameliorates disease pathology in models of AD HDAC11 mediates CGRP receptor function in AD HDAC11 is a pivotal regulator in lipid metabolism by LXR{beta}/ABCA1 signaling The HDAC11/LXR{beta}/ABCA1 axis is conserved in AD humans and mice

neuroscience↗

Arctic-Atlantic gradient shaped PFAS exposure variability in sympatric guillemot species off Iceland

Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants of growing environmental concern in marine ecosystems. While previous approaches have focused on mean concentrations, we here propose treating PFAS exposure variability as an ecological signal rather than statistical noise. To examine this variability-as-signal hypothesis, we analysed PFAS concentrations in plasma and stable isotopes in plasma and red blood cells from 112 individuals of two sympatric guillemot species (Uria lomvia, n = 45; U. aalge, n = 67) across five Icelandic colonies during the 2018 breeding season. The dual-tissue isotopic approach allowed us to assess foraging consistency across different temporal scales, providing context for interpreting PFAS exposure patterns. PFAS variability was dominated by two compound groups: Long-chain perfluoroalkyl carboxylic acids (PFCAs, 79% of variance) and perfluorooctane sulfonate (PFOS, 13% of variance). We standardised individual variability into Z-scores to quantify individual expression of these exposure patterns, revealing three distinct variability clusters corresponded with oceanographic transitions between Arctic and Atlantic waters. Segmented regression analysis showed that significant threshold effects at the Arctic-Atlantic habitats (distinguished by isotopic breakpoints {delta}13Cconsist = 0.19, {delta}15Nconsist = 0.00) with contrasting ecological drivers: PFOS variability responded to habitat-driven shifts ({delta}13C, p < 0.01) and PFCA variability to trophic indicators ({delta}15N). Both species exhibited similar PFAS patterns when foraging in the same water masses, with notable exceptions where niche partitioning occurred at oceanographic boundaries. Our findings demonstrate that water mass characteristics and foraging strategies create structured PFAS variability patterns that reflect local ecological adaptations within broader geographical gradients. This variability-focused framework reveals ecological dimensions of contamination that complement traditional mean-based approaches and may improve understanding of contaminant risks in rapidly changing marine ecosystems.

ecology↗

A Bayesian Approach for Identifying Driver Mutations within Oncogenic Pathways through Mutual Exclusivity

Distinguishing driver mutations from the large background of passenger mutations remains a major challenge in cancer genomics. Evidence-based approaches to nominate driver mutations are often limited by the availability of experimental or clinical validation for specific variants. As clinical sequencing becomes integrated into patient care, computational methods provide powerful opportunities to analyze expanding genomic datasets and identify functional candidates beyond the current knowledge base. Among various analytical frameworks, mutual exclusivity, the observation that mutations in two or more genes tend not to co-occur within the same tumor, has been particularly attractive. Building on this principle, we propose BayesMAGPIE, a refined version of a statistical method, MAGPIE, developed previously for identifying driver genes within oncogenic pathways. The new method introduces two key innovations. First, it incorporates information on mutation type using a Bayesian hierarchical modeling framework, enabling the distinction between potential differences in functional effects among variants within the same gene, thereby improving the accuracy of driver identification. Second, it models gene-specific driver frequencies with a Dirichlet prior which effectively controls the sparsity of the inferred driver set and aligns with the biological expectation that most tumor types are driven by a small number of genes. We evaluate BayesMAGPIE through extensive simulation studies to assess its estimation bias and accuracy in driver identification, and benchmark its performance against MAGPIE using TCGA data from eight cancer types.

bioinformatics↗

Conformational Dynamics and Catalytic Backups in a Hyper-Thermostable Engineered Archaeal Protein Tyrosine Phosphatase

Protein tyrosine phosphatases (PTPs) are a family of enzymes that play important roles in regulating cellular signaling pathways. The activity of these enzymes is regulated by the motion of a catalytic loop that places a critical conserved aspartic acid side chain into the active site for acid-base catalysis upon loop closure. These enzymes also have a conserved phosphate binding loop that is typically highly rigid and forms a well-defined anion binding nest. The intimate links between loop dynamics and chemistry in these enzymes make PTPs an excellent model system for understanding the role of loop dynamics in protein function and evolution. In this context, archaeal PTPs, which have evolved in extremophilic organisms, are highly understudied, despite their unusual biophysical properties. We present here an engineered chimeric PTP (ShufPTP) generated by shuffling the amino acid sequence of five extant hyperthermophilic archaeal PTPs. Despite ShufPTPs high sequence similarity to its natural counterparts, ShufPTP presents a suite of unique properties, including high flexibility of the phosphate binding P-loop, facile oxidation of the active site cysteine, mechanistic promiscuity, and most notably, hyperthermostability, with a denaturation temperature likely >130 {degrees}C (>8 {degrees}C higher than the highest recorded growth temperature of any archaeal strain). Our combined structural, biochemical, biophysical and computational analysis provides insight both into how small steps in evolutionary space can radically modulate the biophysical properties of an enzyme, and showcase the tremendous potential of archaeal enzymes for biotechnology, to generate novel enzymes capable of operating under extreme conditions. Table of Contents Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/645524v3_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@186bfccorg.highwire.dtl.DTLVardef@19a265borg.highwire.dtl.DTLVardef@14c526corg.highwire.dtl.DTLVardef@1b75920_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

mRNA lipid nanoparticle-incorporated nanofiber-hydrogel composite generates a local immunostimulatory niche for cancer immunotherapy

Hydrogel materials have emerged as versatile platforms for various biomedical applications. Notably, the engineered nanofiber-hydrogel composite (NHC) has proven effective in mimicking the soft tissue extracellular matrix, facilitating substantial recruitment of host immune cells and the formation of a local immunostimulatory microenvironment. Leveraging this feature, here we report an mRNA lipid nanoparticle (LNP)-incorporated NHC microgel matrix, termed LiNx, by incorporating LNPs loaded with mRNA encoding tumour antigens. Harnessing the potent transfection efficiency of LNPs in antigen-presenting cells (APCs), LiNx demonstrates remarkable immune cell recruitment, antigen expression and presentation, and cellular interaction. These attributes collectively create an immunostimulating milieu and yield a potent immune response achievable with a single dose, comparable to the conventional three-dose LNP immunization regimen. Further investigations reveal that the LiNx not only generates heightened Th1 and Th2 responses but also elicits a distinctive Type 17 T helper cell-mediated response pivotal for bolstering antitumour efficacy. Our findings elucidate the mechanism underlying LiNxs role in potentiating antigen-specific immune responses, presenting a new strategy for cancer immunotherapy.

bioengineering↗

Improving Accuracy of Somatic Mutation Profiling in Large Epidemiologic Studies: Addressing Cases without Matched Normal Samples

Ideally, detection of somatic mutations in a tumor is accomplished using a patient-matched sample of normal cells as the benchmark. In this way somatic mutations can be distinguished from rare germline mutations. In large retrospective studies, archival tissue collection can pose challenges in obtaining samples of normal DNA. In this article we propose a protocol that improves somatic mutation analysis in the absence of a matched normal sample. The method was motivated by the InterMEL study, a large-scale epidemiologic investigation involving multiomic, multi-institutional genomic profiling of 1000 primary melanoma samples. The key insight for accomplishing improved mutation calling is the fact that germline mutations should produce a variant allele frequency (VAF) of around 50%. While a similar VAF of 50% would also be expected for somatic mutations in pure tumor samples, typically the tumor purity is much less than 50%, resulting in a considerably lower VAF. Making use of a technique that can simultaneously estimate both tumor purity and VAF from tumor-only samples we have developed a method for better distinguishing somatic versus germline variants. Based on 137 melanomas from the InterMEL Study with matched normal tissue to provide a gold standard we show that the conventional pipeline using a panel of (unmatched) normal samples has a false positive rate of 15.6% and a false negative rate of 3.5%. Our new technique improves these error rates to 6.4% and 2.1%, respectively.

genomics↗

Decoding Spatial Tissue Architecture: A Scalable Bayesian Topic Model for Multiplexed Imaging Analysis

Recent progress in multiplexed tissue imaging is advancing the study of tumor microenvironments to enhance our understanding of treatment response and disease progression. Cellular neighborhood analysis is a popular computational approach for these complex image data. Despite its popularity, there are significant challenges, including high computational demands that limit feasibility for largescale applications and the lack of a principled strategy for integrative analysis across images. This absence hampers the precise and consistent identification of spatial features and tracking of their dynamics over disease progression. To overcome these challenges, we introduce SpatialTopic, a spatial topic model designed to decode high-level spatial architecture across multiplexed tissue images. SpatialTopic integrates both cell type and spatial information within a topic modelling framework, originally developed for natural language processing and adapted for computer vision. Spatial information is incorporated into the flexible design of documents, representing densely overlapping regions in images. We employ an efficient collapsed Gibbs sampling algorithm for model inference. We benchmarked the performance against five state-of-the-art algorithms through various case studies using different single-cell spatial transcriptomic and proteomic imaging platforms across different tissue types. We show that SpatialTopic is highly scalable on large-scale image datasets with millions of cells, along with high precision and interpretability. Our findings demonstrate that SpatialTopic consistently identifies biologically and clinically significant spatial "topics" such as tertiary lymphoid structures (TLSs) and tracks dynamic changes in spatial features over disease progression. Its computational efficiency and broad applicability across various molecular imaging platforms will enhance the analysis of large-scale tissue imaging datasets.

bioinformatics↗

Autism and Intellectual Disability-Associated MYT1L Mutation Alters Human Cortical Interneuron Differentiation, Maturation, and Physiology

MYT1L is a neuronal transcription factor highly expressed in the developing and adult brain. While pathogenic MYT1L mutation causes neurodevelopmental disorders, these have not been characterized in human models of neurodevelopment. Here, we defined the consequences of pathogenic MYT1L mutation in human pluripotent stem cell-derived cortical interneurons. During differentiation, mutation reduced MYT1L expression and increased progenitor cell cycle exit and neuronal differentiation and synapse-related gene expression, morphological complexity, and synaptic puncta formation. Conversely, interneuron maturation was compromised, while variant neurons exhibited altered sodium and potassium channel activity and reduced function in electrophysiological analyses. CRISPRi-based knockdown similarly impaired interneuron differentiation and maturation, supporting loss of function-based effects. We further defined MYT1L genome-wide occupancy in interneurons and related this to the transcriptomic dysregulation resulting from MYT1L mutation, to identify direct targets that could mediate these phenotypic consequences. Together, this work delineates contributors to the etiology of neurodevelopmental disorders resulting from MYT1L mutation.

developmental biology↗

Spatial Immunophenotyping from Whole-Slide Multiplexed Tissue Imaging Using Convolutional Neural Networks

The multiplexed immunofluorescence (mIF) platform enables biomarker discovery through the simultaneous detection of multiple markers on a single tissue slide, offering detailed insights into intratumor heterogeneity and the tumor-immune microenvironment at spatially resolved single cell resolution. However, current mIF image analyses are labor-intensive, requiring specialized pathology expertise which limits their scalability and clinical application. To address this challenge, we developed CellGate, a deep-learning (DL) computational pipeline that provides streamlined, end-to-end whole-slide mIF image analysis including nuclei detection, cell segmentation, cell classification, and combined immuno-phenotyping across stacked images. The model was trained on over 750,000 single cell images from 34 melanomas in a retrospective cohort of patients using whole tissue sections stained for CD3, CD8, CD68, CK-SOX10, PD-1, PD-L1, and FOXP3 with manual gating and extensive pathology review. When tested on new whole mIF slides, the model demonstrated high precision-recall AUC. Further validation on whole-slide mIF images of 9 primary melanomas from an independent cohort confirmed that CellGate can reproduce expert pathology analysis with high accuracy. We show that spatial immuno-phenotyping results using CellGate provide deep insights into the immune cell topography and differences in T cell functional states and interactions with tumor cells in patients with distinct histopathology and clinical characteristics. This pipeline offers a fully automated and parallelizable computing process with substantially improved consistency for cell type classification across images, potentially enabling high throughput whole-slide mIF tissue image analysis for large-scale clinical and research applications.

bioinformatics↗

Structural Insights into the Roles of PARP4 and NAD+ in the Human Vault Cage

Vault is a massive ribonucleoprotein complex found across Eukaryota. The major vault protein (MVP) oligomerizes into an ovular cage, which contains several minor vault components (MVCs) and is thought to transport transiently bound "cargo" molecules. Vertebrate vaults house a poly (ADP-ribose) polymerase (known as PARP4 in humans), which is the only MVC with known enzymatic activity. Despite being discovered decades ago, the molecular basis for PARP4s interaction with MVP remains unclear. In this study, we determined the structure of the human vault cage in complex with PARP4 and its enzymatic substrate NAD+. The structures reveal atomic-level details of the protein-binding interface, as well as unexpected NAD+-binding pockets within the interior of the vault cage. In addition, proteomics data show that human vaults purified from wild-type and PARP4-depleted cells interact with distinct subsets of proteins. Our results thereby support a model in which PARP4s specific incorporation into the vault cage helps to regulate vaults selection of cargo and its subcellular localization. Further, PARP4s proximity to MVPs NAD+-binding sites could support its enzymatic function within the vault.

biochemistry↗