Biology subjects

Zhao, L.

Publications and source records attributed to Zhao, L..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

Plant-specific adaptations of the CDC48 unfoldase

Targeted protein degradation through the CDC48 unfoldase enables the maintenance and rapid adaptation of proteomes across eukaryotes. However, the profound differences between animals, fungi, and plants are expected to have led to a significant adaptation of the CDC48-mediated degradation. While animal and fungal CDC48 systems have shown structural and functional preservation, such analysis is lacking for plants. We determined the structural and functional characteristics of Arabidopsis thaliana CDC48A in various states and bound to the target-identifying cofactors UFD1 and NPL4. Our analysis reveals several features that distinguish AtCDC48 from its animal and yeast counterparts, despite an 80% sequence identity. Key features are that AtCDC48A displays distinct domain dynamics and interacts differently with AtNPL4. Moreover, AtNPL4 and AtUFD1 do not form an obligate heterodimer, but independently bind to AtCDC48A and mediate target degradation; however, their joint action is synergistic. An evolutionary analysis supports that these Arabidopsis features are conserved across plants and represent the ancestral state of eukaryotic CDC48 systems. Jointly, our findings support that plant CDC48 retains a greater modular and combinatorial cofactor usage, highlighting a specific adaptation of targeted protein degradation in plants.

plant biology↗

bioRxiv2025

The lysine side chain's swing motion in AapA1 toxin promotes water transport through transmembrane pores

The rising antibiotic resistance of Helicobacter pylori and the emergence of multi-drug-resistant strains pose significant challenges to its eradication. Understanding the molecular mechanisms driving this resistance is critical. This study investigates how AapA1, a toxin protein, may inhibit H. pylori growth and cause morphological changes by forming transmembrane pores in its inner membrane. Using experimental data and molecular dynamics simulations, we analyzed the pore structure and its formation mechanism. Results show that AapA1 forms pores on liposomes and exists stably in the membrane as -helices through different multimers, creating hydrophilic pores of varying sizes. Dynamic oscillation of K16/23 side chains in the membrane affects water transport through these pores, and restricting their movement significantly reduces transport. AapA1 monomers adopt three distinct conformations, with the K16/23 residues showing an up-down swing motion, potentially facilitating accelerated transport of substances. This study provides a new perspective on the dynamic structure-function relationship of AapA1-membrane interaction and highlights the role of positively charged residues in AapA1. Understanding the multimeric AapA1-membrane structure and the mechanism underlying AapA1-induced transmembrane pores is particularly crucial to develop new drugs and treatment options to reduce drug resistance emergence and combat any new emergence development.

biophysics↗

bioRxiv2025

Automated Discovery of Therapeutic Biomaterial for Renally Impaired Hyperuricemia Patients by Natural Language Processing and Machine Learning

The exponential growth of scientific publications presents opportunities for researchers to identify valuable knowledge, especially in the highly interdisciplinary field --- biomaterials, where exploiting possible connections between unmet clinical needs and materials properties from literatures is crucial. However, with traditional literature reading, it is extremely challenging to marry unmet clinical needs with existing materials reported for different applications or other purposes. Here, to provide a not-renally cleared therapeutics for renally impaired hyperuricemia patients, we designed a multi-tiered framework MatWISE that fuses state-of-the-art natural language processing, semantic relationship mapping, and machine learning to automate the complex process of material discovery from a sea of scientific literatures published until December of 2022, and successfully identified and optimized {delta}-MnO2 into an orally administered, nonabsorbable uric acid (UA) lowering biomaterial. {delta}-MnO2 had superior serum and urine UA-lowering effect in three hyperuricemia mouse models, by comparing with a standard of care drug. {delta}-MnO2 is highly promising to serve as a safe and effective UA-lowering drug for renally impaired hyperuricemia patients. We demonstrated a new research paradigm for biomaterials that combining state-of-the-art machine learning techniques and a handful of experiments to discover a translationally relevant material from the massive existing research, for an unmet clinical need.

biochemistry↗

bioRxiv2025

NtLLG4-mediated unconventional polar exocytosis of NtPPME1 coordinates cell wall rigidity and membrane dynamics to control pollen tube integrity

Plant fertilization relies on controlled pollen tube growth that integrates membrane dynamics and cell wall expansion. We previously identified an unconventional exocytic pathway wherein Golgi-derived secretory vesicles (GDSVs) bypass the trans-Golgi network to deliver Nicotiana tabacum pectin methylesterase 1 (NtPPME1), thereby modulating cell wall rigidity. However, the mechanisms linking this patwhay with membrane dynamics and signaling remain elusive. Here, we used cryo-FIB-SEM and 3D tomography to identified GDSVs as a distinct vesicle population at the pollen tube tip. We further demonstrated that tobacco LORELEI-like-GPI-anchored protein 4 (NtLLG4), a key signaling molecule controlling membrane dynamics and integrity, functions as a receptor for NtPPME1, regulating its polar exocytosis via GDSVs to control cell wall stiffness. Furthermore, we identified trafficking signals which direct the unconventional exocytosis of NtPPME1 across intracellular organelles. Our findings reveal a crucial mechanism coupling cell wall rigidity with membrane signaling to control pollen tube growth and integrity during fertilization. TeaserWe reveal a mechanism coupling cell wall rigidity with member signaling to control pollen tube growth and integrity during plant fertilization.

plant biology↗

bioRxiv2025

A distinctive subset of microglia positioned at the paraventricular zone are dedicated to cleaning the cerebrospinal fluid

The interconnected ventricles in the central nervous system are filled with cerebrospinal fluid (CSF) which serves multifaceted roles including bring away metabolic wastes. However, whether there is an inherent "dislodging" mechanism, in addition to CSF drainage and reabsorption, at play for the removal of microparticles in the CSF is unclear. In this study, we identified a subset of microglia distributed in close proximity to the ependymal wall of ventricles. They differed from parenchymal microglia in morphology, behaviors and transcriptomes. In particular, the paraventricular microglia extended transependymal dendrites into the lumen of ventricles and were proficient in sequestering and phagocytosing intraventricular exogenous particles when present. A specific removal of the paraventricular microglia led to an acute ventriculomegaly due to an increased colloid osmotic pressure in the CSF resulting from protein accumulation. Thus, we identified the paraventricular microglia as specific guardians in monitoring and cleaning the CSF.

immunology↗

bioRxiv2025

A novel virus vB_PshM_Y4 with low similarity to both cultured and uncultured viruses

Viruses are the abundant and diverse biological entities on the Earth. During past decades, our knowledge about genomic diversity of viruses has been greatly expanded through high-throughput sequencing. However, whether traditional isolation method could detect virus that could not be identified by high-throughput sequencing is still unknown. In this study, a novel virus, vB_PshM_Y4, infecting Pseudoalteromonas shioyasakiensis, which is an opportunistic pathogen of economically important marine species, was isolated. After comparing vB_PshM_Y4 with the over 15 million genomes of both cultivated and uncultivated viruses in the NCBI and IMG/VR v4 datasets, no similar genome was identified. This suggests that viral isolation methods can detect novel viruses that may not be identified through high-throughput sequencing. Transmission electron microscopy showed that vB_PshM_Y4 exhibits the myoviral morphology. The virus possesses a double-stranded DNA genome that is 158,231 bp in length, with a G+C content of 30.92%, and contains 226 open reading frames (ORFs). Six ORFs were identified as putative auxiliary metabolic genes (AMGs). Phylogenetic tree and gene content-based network analyses indicated that vB_PshM_Y4 may represent a novel viral species within an unknown family of the Caudoviricetes class. Additionally, biogeographical distribution analysis showed that vB_PshM_Y4 were mainly detected in the Arctic and temperate and tropical epipelagic zones with low abundance. ImportanceThis study suggests that viral isolation could detect novel virus that could not be identified through high-throughput sequencing, contributed to a deeper understanding of the genetic diversity and distribution of Pseudoalteromonas viruses, and offered valuable insights into the prevention and control of opportunistic pathogenic bacteria affecting economically important marine organisms.

microbiology↗

bioRxiv2025

Evolution of chronic lymphocytic leukemia after allogeneic stem cell transplant

Allogeneic stem cell transplant (alloSCT) for patients with relapsed/refractory chronic lymphocytic leukemia (CLL) can result in cure in some patients. Analogous to chemotherapy and targeted therapy, we hypothesized that allogeneic cellular immunotherapies, including alloSCT and donor lymphocyte infusion (DLI), would impact malignant evolution through the application of selective immunologic pressure with reciprocal changes in the T cell compartment. We tested a cohort of 24 patients treated with HLA-matched alloSCT +/- DLI, two mediators of the graft versus leukemia (GVL) effect. Comparison of pre-alloSCT samples revealed that a key difference between responders (n=13) and non-responders (n=11) is the cellularity of leukemic cells. We further mapped mutational trajectories of tumor cells by whole exome sequencing (WES) of sort-purified CLL in 11 post-transplant relapsed patients and found evidence of subclonal leukemic evolution in 8/11 patients after nonmyeloablative human leukocyte antigen (HLA)-matched alloSCT. Different patterns of CLL evolution were observed, and these changes included putative CLL drivers in every case. To investigate the presence of immune-related variants in patients, we collected 19 T cell co-culture CRISPR datasets and identified the top positive and negative regulators of cancer cells response to T-cell-dependent killing. We found that most mutations linked to T-cell killing emerged after allo-SCT treatment, suggesting that selective pressures from the GVL effect may drive the evolution of these mutations. Together, these data identify cellular homogeneity as a key biomarker for susceptibility to GVL-driven immunity in CLL and illustrate how the leukemic cells further evolve to evade immunosurveillance. SIGNIFICANCEThe impact of allogeneic stem cell transplant (alloSCT) on subclonal leukemia evolution remains poorly understood. By performing whole exome sequencing (WES) on pre- and post-alloSCT patient samples, we reveal different patterns of CLL evolution and potential immune-related driver genes influencing CLL relapse and refractory disease post-alloSCT.

cancer biology↗

bioRxiv2025

Sequencing-based Spatial Transcriptomics with scRNA-seq Sensitivity

The advent of spatial transcriptomics has dramatically expanded our ability to study the vast network of cell-cell interactions at the molecular level in tissue. Among current methods, sequencing-based approaches have great potential in discovering because of its unbiased capture. In the last couple of years, the spatial resolution for the capture addresses has been significantly improved from 100 m to <1 m, well below the size of a mammalian cell. However, the capture efficiency has always been a pain point, [~]one order of magnitude lower than that of single cell RNA sequencing (scRNA-seq). The low capture efficiency limits the depth and breadth of its applications in the study of complex biological systems and diseases. Here, we introduce Salus Spatial transcriptomic system (Salus-STS), which provides [~]1 m capture resolution and a capture efficiency [~]1 order of magnitude higher than other current methods. Analysis with sub-cellular resolution becomes practical for sequencing-based spatial transcriptomics.

molecular biology↗

bioRxiv2024

Gene regulatory networks and essential transcription factors for de novo originated genes

The regulation of gene expression is crucial for the functional integration of evolutionarily young genes, particularly those that emerge de novo. However, the regulatory programs governing the expression of de novo genes remain unknown. To address this, we applied computational methods to single-cell RNA sequencing data, identifying key transcription factors likely instrumental in regulating de novo genes. We found that transcription factors do not have the same propensity for regulating de novo genes; some transcription factors contain more de novo genes than others in their regulon. Leveraging genetic and genomic tools in Drosophila, we further examined the role of two key transcription factors and the regulatory architecture of novel genes. Our findings identify key transcription factors associated with the expression of de novo genes and provide new insights into how modifications in existing transcription factors enable the emergence, maintenance, and regulation of de novo genes.

evolutionary biology↗

bioRxiv2024

A precision oncology-focused deep learning framework for personalized selection of cancer therapy

Precision oncology matches tumors to targeted therapies based on the presence of actionable molecular alterations. However, most tumors lack actionable alterations, restricting treatment options to cytotoxic chemotherapies for which few data-driven prioritization strategies currently exist. Here, we report an integrated computational/experimental treatment selection approach applicable for both chemotherapies and targeted agents irrespective of actionable alterations. We generated functional drug response data on a large collection of patient-derived tumor models and used it to train ScreenDL, a novel deep learning-based cancer drug response prediction model. ScreenDL leverages the combination of tumor omic and functional drug screening data to predict the most efficacious treatments. We show that ScreenDL accurately predicts response to drugs with diverse mechanisms, outperforming existing methods and approved biomarkers. In our preclinical study, this approach achieved superior clinical benefit and objective response rates in breast cancer patient-derived xenografts, suggesting that testing ScreenDL in clinical trials may be warranted.

cancer biology↗

bioRxiv2024

Environmentally-relevant doses of bisphenol A and S exposure in utero disrupt germ cell programming across generations resolved by single nucleus multi-omics

BackgroundExposure to endocrine-disrupting chemicals (EDCs), such as bisphenol A (BPA), disrupts reproduction across generations. Germ cell epigenetic alterations are proposed to bridge transgenerational reproductive defects resulting from EDCs. Previously, we have shown that prenatal exposure to environmentally relevant doses of BPA or its substitute, BPS, caused transgenerationally maintained reproductive impairments associated with neonatal spermatogonial epigenetic changes in male mice. While epigenetic alterations in germ cells can lead to transgenerational phenotypic variations, the mechanisms sustaining these changes across generations remain unclear. ObjectivesThis study aimed to systematically elucidate the mechanism of transgenerational inherence by prenatal BPA and BPS exposure in the murine germline from F1 to F3 generations at both transcriptomic and epigenetic levels. MethodsBPA or BPS with doses of 0 (vehicle control), 0.5, 50, or 1000 {micro}g/kg/b.w./day was orally administered to pregnant CD-1 females (F0) from gestational day 7 to birth. Sperm counts and motility were examined in F1, F2, and F3 adult males. THY1+ germ cells on postnatal day 6 from F1, F2, and F3 males at a dose of 50 {micro}g/kg/b.w./day were used for analysis by single-nucleus (sn) multi-omics (paired snRNA-seq and snATAC-seq on the same nucleus). ResultsPrenatal exposure to BPA and BPS with 0.5, 50, and 1000 {micro}g/kg/b.w./day reduced sperm counts in mice across F1 to F3 generations. In the F1 neonatal germ cells, ancestral BPA or BPS exposure with 50 {micro}g/kg/b.w./day resulted in increased differentially expressed genes (DEGs) associated with spermatogonial differentiation. It also disrupted the balance between maintaining the undifferentiated and differentiating spermatogonial populations. Differentially accessible peaks (DAPs) by snATAC-seq were primarily located in the promoter regions, with elevated activity of key transcription factors, including SP1, SP4, and DMRT1. Throughout F1-F3 generations, biological processes related to mitosis/meiosis and metabolic pathways were substantially up-regulated in BPA-or BPS-exposed groups. While the quantities of DEGs and DAPs were similar in F1 and F2 spermatogonia, with both showing a significant reduction in F3. Notably, approximately 80% of DAPs in F1 and F2 spermatogonia overlapped with histone post-translational modifications linked to transcription activation, such as H3K4me1/2/3 and H3K27ac. Although BPA exerted more potent effects on gene expression in F1 spermatogonia, BPS induced longer-lasting effects on spermatogonial differentiation across F1 to F3 males. Interestingly, DMRT1 motif activity was persistently elevated across all three generations following ancestral BPA or BPS exposure. DiscussionOur work provides the first systematic analyses for understanding the transgenerational dynamics of gene expression and chromatin landscape following prenatal exposure to BPA or BPS in neonatal spermatogonia. These results suggest that prenatal exposure to environmentally relevant doses of BPA or BPS alters chromatin accessibility and transcription factor motif activities, consequently contributing to disrupted transcriptional levels in neonatal germ cells, and some are sustained to F3 generations, ultimately leading to the reduction of sperm counts in adults.

pharmacology and toxicology↗

bioRxiv2024

DRUGSYNC: Prediction of Synergistic Drug Combinations Using GCN Graph Convolutional Network based and Pre-learned Drug-induced Gene Expression Profiles

Drug-drug synergy (DDS) is crucial for identifying novel and effective drug combinations. With the accumulation of experimental data (DrugCombDB) and the uprising of deep learning approaches, many efforts have been made to computationally predict effective drug pairs. However, most models had limited success, with the highest ROC AUC of 0.65 for predicting pairs of unseen drugs. Drug-induced gene expressions profiles (DGEP) from datasets like LINCS L1000 offer a robust proxy to describe drug effects. However, overlap between DrugCombDB and experimental DGEP data is sparse only [~]2%. To address these limitations, we propose the DRUGSYNC (Drug Response and Utilization for Graph-based SYNergy Classification) prediction framework that leverages pre-learned drug-target interaction (DTI) and pre-learned DGEP as features. Graph Convolutional Network (GCN) was used to represent the inherent network of genetic interactions. Our pre-learned DGEP achieved 0.877 Pearson correlation coefficients (PCC). Furthermore, our framework excels by integrating pre-learned DGEP and DTI of paired drugs for DDS prediction, achieving superior performance over benchmark technologies. Notably, it demonstrates exceptional accuracy in predicting interactions between unseen drugs, with an ROC AUC score of 0.854. The analysis further emphasized the importance of accurate DGEP predictions. This method can be extended to any cell lines.

bioinformatics↗

bioRxiv2024

CEACAM1 Targets ABCA1 to Mediate Atrial Fibrillation via Lipophagy-Dependent Ferroptosis

Atrial fibrillation (AF) is one of the most common arrhythmias, imposing a significant burden on individuals due to its association with cerebrovascular events. The mechanisms underlying AF involve cardiac structural remodeling, electrical remodeling, and metabolic remodeling, with oxidative stress playing a crucial role. Our previous studies demonstrated that upregulation of CEACAM1 can increase oxidative stress, inhibit cell proliferation, and potentially contribute to cellular damage, while ferroptosis is closely associated with AF. In this study, we observed a significant increase in CEACAM1 expression in an AF model. Knocking out CEACAM1 revealed changes in mitochondrial membrane potential, reactive oxygen species (ROS) levels, intracellular Ca2+ concentration, channel proteins, and glycolipid metabolic enzymes. This knockout reversed electrical, structural, and metabolic remodeling in AF. Further investigation showed that CEACAM1 knockout inhibited ferroptosis, as evidenced by ferroptosis-related indicators. Using colocalization analyses of lipid droplets, lysosomes, and autophagosomes, we discovered that CEACAM1 knockout suppressed autophagy and lipophagy during AF. Supplementation with free fatty acids (FFAs) in the AF model post-CEACAM1 knockout suggested that the inhibition of ferroptosis was linked to a reduction in FFAs. Transcriptomic and non-targeted metabolomic analyses, along with ABCA1 interference studies, indicated that CEACAM1 knockout mitigates AF by promoting ABCA1 expression. In summary, CEACAM1 targets ABCA1 to alleviate AF through the regulation of lipophagy-dependent ferroptosis, as demonstrated in both cellular and animal models. BackgroundFerroptosis is a regulated form of cell death, but its connection with atrial fibrillation(AF) remains unclear. Since CEACAM1 knockout reduces oxidative stress and protects cells, we investigated the relationship among CEACAM1, ferroptosis, and AF to uncover the regulatory mechanisms of ferroptosis in AF. MethodsWe established AF models using HL-1 cells, human pluripotent stem cells, and rats. CEACAM1 expression levels were assessed in these models, along with changes in mitochondrial membrane potential, ROS levels, intracellular Ca2+ concentration, channel proteins, glycolipid metabolic enzymes, and ferroptosis-related indicators following CEACAM1 knockout. Through transcriptomics, non-target metabolomics, and immunoprecipitation screening, we identified ABCA1 as a downstream gene of CEACAM1 involved in protecting against AF. Subsequently, ABCA1 interference experiments were conducted, and colocalization analyses of lipid droplets, lysosomes, and autophagosomes were performed after the application of ferroptosis activators, lipophagy inhibitors, and lipophagy activators. FFAs were added to the AF model to evaluate changes in lipophagy and ferroptosis following CEACAM1 knockout. ResultsIn the AF model using HL-1 myocytes, CEACAM1 knockout reverse electrical, structural, and metabolic remodeling while inhibiting ferroptosis, with ABCA1 as a downstream gene. In the AF model derived from pluripotent stem cells differentiated into atrial myocytes, CEACAM1 knockout suppressed autophagy and lipophagy during AF, thereby inhibiting ferroptosis, which correlated with reduced FFA release. This process was regulated by ABCA1. In the rat AF model, ABCA1, identified as a downstream gene of CEACAM1, was further confirmed to inhibit ferroptosis by regulating FFA levels. ConclusionThis study reveals that CEACAM1 knockout inhibits ferroptosis in AF models by upregulating ABCA1 and reducing FFA levels, providing a novel regulatory mechanism for ferroptosis in AF. O_FIG O_LINKSMALLFIG WIDTH=172 HEIGHT=200 SRC="FIGDIR/small/625561v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@809c82org.highwire.dtl.DTLVardef@1a339d6org.highwire.dtl.DTLVardef@12a20d4org.highwire.dtl.DTLVardef@d14927_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Cross-tissue Graph Attention Networks for Semi-supervised Gene Expression Prediction

High-throughput biotechnologies have significantly advanced precision medicine by enabling the exploitation of global gene expression patterns to enhance our understanding of disease etiology, progression, and treatment options. However, the tissue-specific nature of gene expression presents a challenge, particularly for less accessible tissues such as the brain, underscoring the need for computational methods to accurately impute gene expression in these critical but hard-to-reach tissues. While several attempts to impute gene expression in tissue-specific contexts have shown promising results, their reliance on regression analysis faces limitations due to the inability to capture complex, nonlinear relationships in gene expression patterns. In contrast, modern machine learning techniques, particularly graph neural networks, have demonstrated superior performance by efficiently modeling the intricate interactions among genes across different tissues. Therefore, we introduce gene expression imputation with Graph Attention Networks (gemGAT), a novel approach leveraging Graph Attention Networks (GATs) to enhance gene expression prediction across different tissues. gemGAT distinguishes itself by predicting the expression of all genes simultaneously, utilizing the full spectrum of genomic data to account for gene co-expressions and non-linear relationships. Validated through extensive experiments with Genotype-Tissue Expression (GTEx) data and a case study from the Alzheimers Disease Neuroimaging Initiative (ADNI), gemGAT demonstrates superior performance over existing methods by efficiently capturing non-linear gene co-expressions. This advancement underscores gemGATs potential to significantly contribute to precision medicine, showcasing its utility in advancing our understanding of gene expression in less accessible tissues.

bioinformatics↗

bioRxiv2024

High-resolution imaging atlas reveals context-dependent role of pancreatic sympathetic innervation in diabetic mice

Gaining a better understanding of how sympathetic nerves impact pancreatic function is helpful for understanding diabetes. However, there is still uncertainty and controversy surrounding the roles of sympathetic nerves within the pancreas. To address this, we utilize high-resolution imaging and advanced three-dimensional (3D) reconstruction techniques to study the patterns of sympathetic innervation and morphology in islets of adult WT and diabetic mice. Our data shows that more than [~]30% /{beta}-cells are innervated by sympathetic nerves in both WT and diabetic mice. Also, sympathetic innervated /{beta}-cells are reduced in DIO mice, whereas sympathetic innervated {beta}-cells are increased in db/db mice. Besides, in situ chemical pancreatic sympathetic denervation (cPSD) improves glucose tolerance in WT and db/db mice, but decreases in DIO mice. In situ cPSD also enhances insulin sensitivity in diabetic mice without affecting WT mice. Overall, our findings advance our comprehension of diabetes by highlighting the distinctive impact of pancreatic sympathetic innervation on glucose regulation. HighlightsPancreatic sympathetic innervation plays an important role in glucose homeostasis. In our study, we systematically investigate sympathetic innervation in the islets of WT and diabetic mice. O_LI45.9% -cells and 31.8% {beta}-cells are innervated by sympathetic nerves in 10-week-old WT mice. C_LIO_LISympathetic innervated /{beta}-cells are reduced in DIO mice, whereas sympathetic innervated {beta}-cells are increased in db/db mice. C_LIO_LIUnlike the core-mantle structure observed in WT and DIO mice, -cells and {beta}-cells are intermixed in db/db mice. C_LIO_LIPancreatic sympathetic denervation elicits varied responses across diabetic models, where it improves glucose tolerance and insulin sensitivity in db/db mice, yet it increases insulin sensitivity but reduces glucose tolerance in DIO mice. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/623708v2_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@183be78org.highwire.dtl.DTLVardef@4dc76borg.highwire.dtl.DTLVardef@5f5ca0org.highwire.dtl.DTLVardef@ba3cc7_HPS_FORMAT_FIGEXP M_FIG Summary of morphological and physiological phenotypes in diabetic mice. All data are normalized to that of WT-10 mice. The numbers of "+" refer to their relative numbers. {uparrow} or {downarrow} refers to increase or decrease, ns refers to "not significant". "-" refers to the experiment has not been carried out. C_FIG

neuroscience↗

bioRxiv2024

Salt-dependent non-catalytic allostery of human USP14-regulated 26S proteasome

USP14, a deubiquitylating enzyme, regulates 26S proteasome function both catalytically and non-catalytically through multiple checkpoints. How USP14 non-catalytically regulates the proteasome activity remains elusive. Here, we combined genetic engineering and cryo-EM to disentangle how USP14 non-catalytically regulates proteasome activity in a salt-dependent manner. By solving 16 high-resolution cryo-EM structures of substrate-engaged human 26S proteasome complexed with a catalytically deficient mutant USP14, we demonstrate that USP14s non-catalytic activity alone can induce parallel pathways of proteasome state transitions, leading to opposing substrate fates. The USP14 mutant allosterically reprograms the AAA-ATPase motor, inducing novel substrate-engaged conformations and filling major gaps in understanding asymmetric ATP-hydrolysis cycling around the ATPase ring. Time-resolved cryo-EM and functional analysis reveal that sodium or potassium promotes substrate-engaged pathways and suppresses USP14 activity for enhanced degradation, uncovering another layer of complexity in proteasome regulation.

biochemistry↗

bioRxiv2024

PACT prevents aberrant activation of PKR by endogenous dsRNA without sequestration

The innate immune sensor PKR for double-stranded RNA (dsRNA) is critical for antiviral defense, but its aberrant activation by cellular dsRNA is linked to various diseases. The dsRNA-binding protein PACT plays a critical yet controversial role in the PKR pathway. We demonstrate that PACT is a direct and specific suppressor of PKR against endogenous dsRNA ligands like inverted-repeat Alu RNAs, which robustly activate PKR in the absence of PACT. PACT-mediated inhibition does not involve competition for dsRNA binding. Instead, PACT impairs PKRs ability to scan along dsRNA--a process necessary for PKR molecules to encounter and autophoshorylate each other for activation. By scanning along dsRNA and directly interacting with PKR, PACT restricts PKRs movement on dsRNA, reducing the likelihood of PKR molecular collisions and subsequent autophosphorylation, effectively inhibiting PKR without sequestering dsRNA. Consequently, PKR inhibition is more robust with longer and less abundant dsRNA, and minimal with abundant or short dsRNA. Thus, PACT functions to adjust the PKR activation threshold for long endogenous dsRNA without altering its inherent activity, revealing new mechanisms for establishing self-tolerance.

biochemistry↗

bioRxiv2024

A new synonym for Viburnum erosum (Viburnaceae) in East China, based on morphological and molecular evidence

The critical observations of living plants in the field, along with the examination of type specimens and protologues, led us to conclude that the key characteristics, including the length of the petiole, stipules and peduncles, as well as the shape of leaves of Viburnum fengyangshanense, all fall within the variation range of V. erosum. Additionally, molecular analysis of nuclear ribosomal internal transcribed spacer (nrITS) and three plastid DNA markers (rbcL, matK and ndhF) indicates that V. fengyangshanense and V. erosum are deeply nested within a clade. Therefore, based on morphological and molecular evidence, it is demonstrated that V. fengyangshanense should be regarded as a new synonym of V. erosum.

plant biology↗