Biology subjects

Cheng, Q.

Publications and source records attributed to Cheng, Q..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

SPP1+ tumor-associated macrophages induce radioresistance of nasopharyngeal carcinoma through crosstalk with the tumor microenvironment

The function and phenotype of tumor-associated macrophages (TAMs) influence the efficacy of radiotherapy. However, the effect of different subsets of TAMs on the radioresistance in nasopharyngeal carcinoma (NPC) still needs to be further explored. This study utilized single-cell RNA sequencing (scRNA-seq) to analyze 120,579 cells obtained from 15 NPC samples. Cell annotation, cell-cell communication analysis, and functional annotation were used to investigate the impact of TAMs on the effectiveness of radiotherapy in NPC patients. Additionally, we employed RNA-seq data and clinical information from many patients, including 24 NPC samples from Zhujiang Hospital, 3,934 samples from patients with a history of radiotherapy, for further validation. We identified a hub TAM subpopulation, SPP1+ TAMs, that induced radioresistance in NPC based on single-cell RNA sequencing (scRNA-seq) data. We combined many public datasets to confirm their prognostic value in radiotherapy patients. We found that SPP1+ TAMs had stronger protumorigenic and immunosuppressive effects in the postradiotherapy recurrent tumor (PRRT) group. SPI1 transcription factor efficiently regulates the expression level of SPP1 in macrophages. In addition, we validated the underlying mechanisms by molecular docking, multiplex immunofluorescence and cellular experiments. In conclusions, by forming an immunosuppressive microenvironment and promoting tumor cell proliferation, SPP1+ TAMs leading to radioresistance and poor clinical prognosis in NPC patients. Targeting SPP1+ TAMs could provide new insights into improving the efficacy of radiotherapy in NPC patients.

cancer biology↗

bioRxiv2024

A Multi-Modal Genomic Knowledge Distillation Framework for Drug Response Prediction

Precision oncology utilizes genomic data to tailor treatment to individuals. Cancer drug sensitivity studies can predict the response levels of different drugs for the same cultured cancer cell line, which is beneficial for personalized medicine. Recent studies have demonstrated that integrating multi-modal genomic data, e.g., gene expression, mutation, copy number alteration, methylation, can provide comprehensive knowledge and improve drug response prediction. Although multimodal genomic profiles are generally available from public datasets, only gene expression data is commonly used in clinical settings. In this study, we propose a framework for privileged information knowledge distillation to transfer knowledge from a multi-modal genomic teacher network, using only gene expression for inference. Specifically, we train a teacher network by feature re-weighting based on inter-modality dependencies and align the inter-sample correlations through our proposed relation-aware differentiation distillation. Experiments on the Genomics of Drug Sensitivity in Cancer (GDSC) dataset demonstrate that our framework improves drug response prediction by about 6% compared to the baseline and outperforms state-of-the-art methods. Transferable studies performed on missing GDSC data and clinical datasets further confirm the feasibility of our model for predicting drug responses using only gene expression data.

bioinformatics↗

bioRxiv2024

A Machine Learning-Based Investigation of Integrin Expression Patterns in Cancer and Metastasis

BackgroundIntegrins, a family of transmembrane receptor proteins, play complex roles in cancer development and metastasis. These roles could be better delineated through machine learning of transcriptomic data to reveal relationships between integrin expression patterns and cancer. MethodsWe collected publicly available RNA-Seq integrin expression from 8 healthy tissues and their corresponding tumors, along with data from metastatic breast cancer. We then used machine learning methods, including t-SNE visualization and Random Forest classification, to investigate changes in integrin expression patterns. ResultsIntegrin expression varied across tissues and cancers, and between healthy and cancer samples from the same tissue, enabling the creation of models that classify samples by tissue or disease status. The integrins whose expression was important to these classifiers were identified. For example, ITGA7 was key to classification of breast samples by disease status. Analysis in breast tissue revealed that cancer rewires co-expression for most integrins, but the co-expression relationships of some integrins remain unchanged in healthy and cancer samples. Integrin expression in primary breast tumors differed from their metastases, with liver metastasis notably having reduced expression. ConclusionsIntegrin expression patterns vary widely across tissues and are greatly impacted by cancer. Machine learning of these patterns can effectively distinguish samples by tissue or disease status.

cancer biology↗

bioRxiv2024

Trapping Devices of Carnivorous Fungus Arthrobotrys oligospora Can Isolate Heat-Triggered Excess Irons

Under low-nutrient conditions, Arthrobotrys oligospora and other NTFs can differentiate their mycelia into specialized trapping devices for capturing prey as their nutritional source. Using energy-dispersive X-ray spectroscopy (EDX) in conjunction with transmission electron microscopy (TEM), we identified that the characteristic electron-dense bodies in trapping devices contained more iron than vacuoles and mitochondria. Meanwhile, fungal mycelial cells used effective desferriferrichromes for iron chelation and storage. Complex bioassays showed that electron-dense bodies represent a novel type of microbial iron storage particle and trapping devices in A. oligospora function as an unprecedented phenotypic system for iron storage. Unexpectedly, all NTFs lack a crucial Ccc1-mediated vacuolar iron detoxification mechanism, which is conserved in most fungi. Inserting the Ccc1 gene cloned from yeast into A. oligospora significantly reduced formation of trapping devices and inhibited nematicidal activity. Notably, Bayesian relaxed molecular clock analysis indicated that the loss of Ccc1-mediated vacuolar iron storage occurred during the Late Paleozoic Ice Age, while the origin of the trapping devices and the acquisition of desferriferrichrome biosynthesis were strongly associated with significantly elevated temperatures. Temperature bioassays demonstrated that the formation of trapping devices is highly temperature-dependent, with free iron content in mycelial cells being inversely proportional to temperature, consistent with that A. oligospora is sensitive to high temperatures and fails to grow above 30{degrees}C. Our findings revealed that global temperature fluctuations are a crucial driver of the genetic evolution of NTFs, as a catalyst for the origin of trapping devices, which are a novel phenotypic indicator of eukaryotic iron overload. Author summaryWe found that a unique group of carnivorous fungi has evolved specialized trapping devices to sequester excess iron, compensating for the absence of the crucial Ccc1-mediated vacuolar iron detoxification pathway, which is conserved in most fungi. Furthermore, we report for the first time that elevated temperature is a non-trophic factor that induces iron overload in eukaryotes, as iron content and composition in fungal mycelia are negatively correlated with temperature. Our findings suggest that nematode-trapping fungi could serve as a potential eukaryotic model for investigating the dynamic regulation mechanisms of iron homeostasis, which could contribute to the development of therapies for iron overload-related diseases in humans. In humans, iron overload leads to tissue damage, particularly in the cardiovascular system. It has long been assumed that iron overload occurs when iron intake is increased over an extended period, either through repeated red blood cell transfusions or enhanced absorption from the gastrointestinal tract. Caucasians are particularly susceptible to iron overload and the complications of hemochromatosis due to a higher incidence of mutations in the homeostatic iron regulation gene within this population. The discovery of eukaryotes exhibiting an iron overload phenotype when exposed to heat holds significant implications for developing treatments and strategies for human iron overload disorders.

evolutionary biology↗

bioRxiv2024

Molecular Architecture of Chitin and Chitosan-Dominated Cell Walls in Zygomycetous Fungal Pathogens by Solid-State NMR

Zygomycetous fungal infections pose an emerging medical threat among individuals with compromised immunity and metabolic abnormalities. Our pathophysiological understanding of these infections, particularly the role of fungal cell walls in growth and immune response, remains limited. Here we conducted multidimensional solid-state NMR analysis to examine cell walls in five Mucorales species, including key mucormycosis causative agents like Rhizopus and Mucor species. We show that the rigid core of the cell wall primarily comprises highly polymorphic chitin and chitosan, with minimal quantities of {beta}-glucans linked to a specific chitin subtype. Chitosan emerges as a pivotal molecule preserving hydration and dynamics. Some proteins are entrapped within this semi-crystalline chitin/chitosan layer, stabilized by the sidechains of hydrophobic amino acid residues, and situated distantly from {beta}-glucans. The mobile domain contains galactan- and mannan-based polysaccharides, along with polymeric -fucoses. Treatment with the chitin synthase inhibitor nikkomycin removes the {beta}-glucan-chitin/chitosan complex, leaving the other chitin and chitosan allomorphs untouched while simultaneously thickening and rigidifying the cell wall. These findings shed light on the organization of Mucorales cell walls and emphasize the necessity for a deeper understanding of the diverse families of chitin synthases and deacetylases as potential targets for novel antifungal therapies.

biophysics↗

bioRxiv2024

Targeted LNPs deliver mRNA encoding IL-15 superagonists to balance efficacy and toxicity in cancer therapy

Interleukin-15 (IL-15) emerges as a promising immunotherapeutic candidate in oncology because of its pivotal role in modulating both innate and adaptive immunity. However, the therapeutic utility remains concern due to the unexpected toxicity. We propose here that the mRNA lipid nanoparticle (mRNA-LNP) system can balance the issue through targeted delivery to increase IL-15 concentration in the tumor area and reduce leakage into the circulation. Utilizing the Structure-driven TARgeting (STAR) platform, we acquired intellectual property LNP vectors for effective and selective mRNA delivery to local (LNPLocal) and to pulmonary (LNPLung). Then the promising IL-15 superagonists mRNAs were obtained through structural optimization and sequence screening, showing better activity compared with benchmarker N-803. Subsequently, the anti-tumor efficacy of IL-15 superagonists mRNAs were evaluated by intratumoural (i.t.) injection and intravenous (i.v.) injection via LNPLocal and LNPLung, respectively. As a result, such superagonists exhibited better anti-tumor activity, less systematic exposure, and less cytokine related risks than N-803. We finally verified the selective delivery and well tolerability of LNPLung in non-human primates (NHPs), confirming the potential for clinical application. This finding may open up new possibilities for the treatment of lung cancers and lung metastasis cancers.

bioengineering↗

bioRxiv2023

THER: Integrative Web Tool for Tumor Hypoxia Exploration and Research

Hypoxia is an important factor in the adaptation of tumor cells to their environment, contributes to their malignant progression, and affects tumor prognosis and drug sensitivity. Although there is a wealth of transcriptomic data stored in public databases, there is a lack of web-based tools for analyzing these data to explore the link between hypoxia and the mechanisms of tumorigenesis and progression. To this end, we have developed an interactive web-based tool called THER, which is designed to help users easily identify potential targets, mechanisms of action and effective drugs for treating hypoxic tumors. THER integrates 63 transcriptomic tumor hypoxia datasets from the Gene Expression Omnibus (GEO) database, covering 3 species, 18 tumor types and 42 cell line types. This web tool provides five modules that allow users to perform differential expression analysis, expression profiling analysis, correlation analysis, enrichment analysis and drug sensitivity analysis on different datasets based on different oxygen statuses. We expect that users will be able to use the tool to identify valuable biomarkers, further reveal the molecular mechanisms of tumor hypoxia, and identify effective drugs, thus providing a scientific basis for tumor diagnosis and treatment. THER is open to all users and can be accessed without login at https://smuonco.shinyapps.io/THER/.

cancer biology↗

bioRxiv2023

A pro-inflammatory stem cell niche drives myelofibrosis through a targetable galectin 1 axis

Myeloproliferative neoplasms are stem cell-driven cancers associated with a large burden of morbidity and mortality. The majority of patients present with early-stage disease, but a substantial proportion progress to myelofibrosis and/or secondary leukemia, advanced cancers with a poor prognosis and high symptom burden. Currently, it remains difficult to predict progression, and we lack therapies that reliably prevent or reverse fibrosis development. A major bottleneck to the discovery of disease-modifying therapies has been an incomplete understanding of the interplay between perturbed cellular and molecular states. Several cell types have individually been implicated, but a comprehensive analysis of myelofibrotic bone marrow is lacking. We therefore mapped the crosstalk between bone marrow cell types in myelofibrotic bone marrow. We found that inflammation and fibrosis are orchestrated by a quartet of immune and stromal cell lineages - with basophils and mast cells creating a TNF signaling hub, communicating with megakaryocytes, mesenchymal stromal cells and pro-inflammatory fibroblasts. We identified the y-galactoside binding protein galectin 1 as a striking biomarker of progression to myelofibrosis and poor survival in multiple patient cohorts, and as a promising therapeutic target, with reduced myeloproliferation and fibrosis in vitro and in vivo and improved survival following galectin 1 inhibition. In human bone marrow organoids, TNF increased galectin 1 expression, suggesting a feedback loop wherein the pro-inflammatory MPN clone creates a self-reinforcing niche, fueling progression to advanced disease. This study provides a valuable resource for studying hematopoietic cell-niche interactions, with broad relevance for cancer-associated inflammation and disorders of tissue fibrosis.

cancer biology↗

bioRxiv2023

A Highly Efficient Aorta-Gonad-Mesonephros-Like Definitive Hemogenic Endothelium From Human Pluripotent Stem Cells

Summary/AbstractHuman pluripotent stem cells are a tremendous tool to model early human development and disease including their use in the in vitro generation of blood cell fates. Hematopoietic progenitors and stem cells are the primary source of blood and the immune system from early development to adulthood and arise through successive waves of hemogenic mesoderm either in the yolk sac or embryo proper. Researchers have long sought a tractable human model for observing and distinguishing these waves of hematopoiesis in the dish for human developmental and disease modeling. Here we report a high-efficiency method for differentiating human pluripotent stem cells into an aorta-gonad-mesonephros-like definitive hemogenic mesoderm capable of giving rise to definitive hematopoietic progenitor and stem cells. The hematopoietic progenitor and stem cells exhibit robust multilineage in vitro colony forming potential. Gene expression analysis and single cell sequencing strongly support the developmental timing and notion that the pluripotent stem cell derived hematopoietic stem and progenitors are strikingly like bone fide hematopoietic stem cells. The hematopoietic progenitors can be subsequently differentiated into polarized macrophage and T-cells in vitro. Minimal silencing was observed upon differentiation of the pluripotent stem cells to hematopoietic lineages when conducting gene editing. Finally, upon engraftment into immunodeficient animals the hematopoietic progenitors and stem cells differentiate into multiple lineages including B-cells, T-cells, NK-cells, and monocytes.

developmental biology↗

bioRxiv2023

Prefrontal projections modulate recurrent circuitry in insular cortex to support short-term memory

Short-term memory (STM) maintains information during a short delay period. How long-range and local connections interact to support STM encoding remains elusive. Here we tackled the problem focusing on long-range projections from medial prefrontal cortex (mPFC) to anterior agranular insular cortex (aAIC) in head-fixed mice performing an olfactory delayed-response task. Optogenetic and electrophysiological experiments revealed behavioral importance of the two regions in encoding STM information. Spike-correlogram analysis revealed strong local and cross-region functional coupling (FC) between memory neurons encoding the same information. Optogenetic suppression of mPFC-aAIC projections during the delay period reduced behavioral performance, the proportion of memory neurons and memory-specific FC within aAIC, whereas optogenetic excitation enhanced all of them. MPFC-to-aAIC projections also bidirectionally modulated efficacy of STM-information transfer, measured by contribution of FC spiking pairs to coding ability of following neurons. Thus, prefrontal projections modulate functional connectivity and coding ability of insular neurons to support short-term memory.

neuroscience↗

bioRxiv2023

Integrated single-cell analysis defines the epigenetic basis of castration-resistant prostate luminal cells

Understanding prostate response to castration and androgen receptor signaling inhibitors (ARSI) is critical to improving long-term prostate cancer (PCa) patient survival. Here we use a multi-omics approach on 229,794 single cells to create a mouse single-cell reference atlas better suited to interpreting mouse prostate biology and castration response. Our reference atlas refines single-cell annotations and provides chromatin context, which, when coupled with mouse lineage tracing demonstrates that the castration-resistant luminal cells are distinct from the pre-existent urethra- proximal stem/progenitor cells. Molecular pathway analysis and therapeutic studies further implicate JUN/FOS, WNT/{beta}-Catenin, FOXQ1, NF{kappa}B, and JAK/STAT pathways as the major drivers of castration- resistant luminal populations with high relevance to human PCa. Importantly, we demonstrate the utility of our datasets, which can be explored through an interactive portal (https://visportal.roswellpark.org/data/tang/), to aid in developing novel combination treatments with ARSI for advanced PCa patients. O_FIG O_LINKSMALLFIG WIDTH=164 HEIGHT=200 SRC="FIGDIR/small/530998v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@8bd384org.highwire.dtl.DTLVardef@1ebc004org.highwire.dtl.DTLVardef@8b4dbforg.highwire.dtl.DTLVardef@19d7052_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

Ancient loss of catalytic selenocysteine spurred convergent adaptation in a mammalian oxidoreductase

Selenocysteine (Sec), the 21st amino acid specified by the genetic code, is a rare selenium-containing residue found in the catalytic site of selenoprotein oxidoreductases. Sec is analogous to the common cysteine (Cys) amino acid but its selenium atom offers physicalchemical properties not provided by the corresponding sulfur atom in Cys. Catalytic sites with Sec in selenoproteins of vertebrates are under strong purifying selection but one enzyme, Glutathione Peroxidase 6 (GPX6), independently exchanged Sec for Cys less than one hundred million years ago in several mammalian lineages. We reconstructed and assayed these ancient enzymes before and after Sec was lost and up to today, and found them to have lost their classic ability to reduce hydroperoxides using glutathione (GSH). This loss of function, however, was accompanied by bursts of amino acid changes in the catalytic domain, with protein sites concertedly changing under positive selection across distant lineages abandoning Sec in GPX6. This demonstrates that when sulfur in Cys impairs catalysis a narrow evolutionary path is followed, with epistasis and pleiotropy leading to convergent evolution and triggering enzymatic properties likely beyond those in classic GPXs. These findings are an unusual example of adaptive convergence towards unexplored oxidoreductase functions during mammalian evolution.

molecular biology↗

bioRxiv2022

PanCanSurvPlot: A Large-scale Pan-cancer Survival Analysis Web Application

The identification of reliable tumor prognostic markers can help clinicians and researchers predict tumor development and patient survival outcomes more accurately, which plays a vital role in clinical diagnosis, treatment effectiveness assessment, and prognostic evaluation. Existing web tools supporting online survival analysis are gradually failing to meet the increasing demands of researchers in terms of the dataset size, richness of survival analysis methods, and diversity of customization features. Therefore, there is an urgent need for a large-scale, one-stop pan-cancer survival analysis web server. We developed PanCanSurvPlot (https://smuonco.shinyapps.io/PanCanSurvPlot/), a Shiny web tool that has incorporated a total of 215 cancer-related datasets from the GEO and TCGA databases, covering nearly 100,000 genes (mRNAs, miRNAs, and lncRNAs), approximately 45,000 samples, 51 different cancer types, and 13 different survival outcomes. The website also provides two cutoff methods based on median and optimal cutpoints. All survival analysis results from the log-rank test and univariate Cox regression are presented in a clear and straightforward summary table. Finally, users can customize color schemes and cutpoint levels to quickly obtain high-quality Kaplan-Meier survival plots that meet publication requirements.

cancer biology↗

bioRxiv2022

Proteomic Landscape of Human Spermatozoa: Optimized Extraction Method and Application

Human spermatozoa proteomics exposed to some physical, biological or chemical stressors is being explored. However, there is a lack of optimized sample preparation methods to achieve in-depth protein coverage for sperm cells. Meanwhile, it is not clear whether antibiotics can regulate proteins to affect sperm quality. Here, we systematically compared a total of six different protein extraction methods based the combination of three commonly used lysis buffers and physical lysis strategies. The urea buffer combined with ultrasonication (UA_ultrasonication) produced the highest protein extraction rate, leading to the deepest coverage of human sperm proteome (5685 protein groups) from healthy human sperm samples. Since the antibiotics, amoxicillin and clarithromycin, have been widely used against H. pylori infection, we conduct a longitudinal study of sperm proteome via data-independent acquisition tandem mass spectrometry (DIA-MS/MS) on an infected patient during on and off therapy with these two drugs. The semen examination and morphological analysis were performed combined with proteomics analysis. Our results indicated that antibiotics may cause an increase in the sperm concentration and the rate of malformed sperm and disrupt proteome expression in sperm. This work provides an optimized extraction method to characterize the in-depth human sperm proteome and to extend its clinical applications.

biochemistry↗

bioRxiv2022

SurvivalML: an integrative platform for the discovery and exploration of prognostic models in multi-center cancer cohorts

Advances in multi-omics and big-data technologies have led to numerous prognostic signatures aimed at improving current clinicopathological staging systems. Due to the lack of reproducibility and independent confirmation, few signatures have been translated into clinical routine. As high-quality datasets accumulate, identifying robust signatures across multiple independent cohorts becomes possible. Nonetheless, inaccurate data retrieval, different versions of genome annotations, disparate expression distributions, difficult data cleaning, inconsistent clinical information, algorithm selection, and parameter tuning have impeded model development and validation in multi-center datasets. Hence, for the first time, we introduced SurvivalML (https://rookieutopia.com/app_direct/SurvivalML/), a web application for helping develop and validate prognostic models across multi-center datasets. SurvivalML included 37,325 samples (253 eligible datasets) with both transcriptome data and survival information from 21 cancer types, which were renewedly and uniformly re-annotated, normalized, and cleaned. This application provided 10 survival machine-learning algorithms for flexibly training models via tuning essential parameters online and delivered four aspects for model evaluation, including Kaplan-Meier survival analysis, time-dependent ROC, calibration curve, and decision curve analysis. Overall, we believe that SurvivalML can serve as an attractive platform for model discovery from multi-center datasets.

bioinformatics↗

bioRxiv2022

BEST: a web application for comprehensive biomarker exploration on large-scale data in solid tumors

SummaryData mining from RNA-seq or microarray data has become an essential part of cancer biomarker exploration. Certain existing web servers are valuable and broadly utilized, but the meta-analysis of multiple datasets is absent. Most web servers only contain tumor samples from the TCGA database with only one cohort for each cancer type, which also means that the analysis results mainly derived from a single cohort are thin and unstable. Indeed, consistent performance across multiple independent cohorts is the foundation for an excellent biomarker. Moreover, many analytical functions researchers require remain adequately unmet by these tools. Thus, we introduce BEST (Biomarker Exploration for Solid Tumors), a web application for comprehensive biomarker exploration on large-scale data in solid tumors. BEST includes more than 50,000 samples of 27 cancer types. To ensure the comparability of genes between different sequencing technologies and the legibility of clinical traits, we re-annotated transcriptome data based on the GRCh38 patch 13 sequences and unified the nomenclature of clinical traits. BEST delivers fast and customizable functions, including clinical association, survival analysis, enrichment analysis, cell infiltration, immunomodulator, immunotherapy, candidate agents, and genomic alteration. Together, our web server provides multiple cleaned-up independent datasets and diverse analysis functionalities, helping unleash the value of current data resources. It is freely available at https://rookieutopia.com/. The bigger pictureBioinformatics web servers enable researchers without computational programming skills to conduct various bioinformatics analyses. However, most web servers only contain tumor samples from the TCGA database with only one cohort for each cancer type, which also means that the analysis results mainly derived from a single cohort are thin and unstable. Thus, we introduce BEST (Biomarker Exploration for Solid Tumors), a web application for comprehensive biomarker exploration on large-scale data in solid tumors. BEST includes more than 50,000 samples of 27 cancer types that have been uniformly re-annotated based on the GRCh38 patch 13 sequences, which ensures the comparability of genes between different sequencing technologies. BEST also offers prevalent functions including clinical association, survival analysis, enrichment analysis, cell infiltration, immunomodulator, immunotherapy, candidate agents, and genomic alteration. Together, BEST provides a curated database and innovative analytical pipelines to explore cancer biomarkers at high resolution.

genomics↗

bioRxiv2022

Creating a thermostable beta-glucuronidase switch for homogeneous immunoassay by disruption of conserved salt bridges at diagonal interfaces

The Escherichia coli beta-glucuronidase (GUS) has been used as a reporter enzyme in molecular biology and has been engineered to enzyme switches for the development of homogeneous biosensors. Here, we developed a thermostable GUS enzyme switch from a thermostable GUS mutant TR3337 by disrupting a conserved salt bridge (H514-E523) between the diagonal subunits of its homotetramer. A combinatorial library (240 variants) was screened by a novel high-throughput strategy, and a mutant DLW (H514D/M516L/Y517W) was found to be a functional enzyme switch in a caffeine-recognizing immunosensor. The molecular dynamics simulations were performed to predict the topology change around position 514, and the sidechain flip of D514 (repulsion with E523) was observed in the DLW mutant. Up to 1.8-fold of the signal-to-background ratio was confirmed when measured at 45 {degrees}C, which makes the DLW mutant a versatile tool for developing the thermostable immunosensors for in vitro and in cellulo applications. Table of contents graphic O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

bioengineering↗

bioRxiv2022

Rabphilin 3A binds the N-peptide of SNAP-25 to promote SNARE complex assembly in exocytosis

Exocytosis of secretory vesicles requires the soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins and small GTPase Rabs. As a Rab3/Rab27 effector protein on secretory vesicles, Rabphilin 3A was implicated to interact with SNAP-25 to regulate vesicle exocytosis in neurons and neuroendocrine cells, yet the underlying mechanism remains unclear. In this study, we have characterized the physiologically relevant binding sites between Rabphilin 3A and SNAP-25. We found that an intramolecular interplay between the N-terminal Rab-binding domain and C-terminal C2AB domain enables Rabphilin 3A to strongly bind the SNAP-25 N-peptide region via its C2B bottom -helix. Disruption of this interaction significantly impaired docking and fusion of vesicles with the plasma membrane in PC12 cells. In addition, we found that this interaction allows Rabphilin 3A to accelerate SNARE complex assembly. Furthermore, we revealed that this interaction accelerates SNARE complex assembly via inducing a conformational switch from random coils to -helical structure in the SNAP-25 SNARE motif. Altogether, our data suggest that promotion of SNARE complex assembly by binding of the C2B bottom -helix of Rabphilin 3A to the N-peptide of SNAP-25 underlies a pre-fusion function of Rabphilin 3A in vesicle exocytosis.

biophysics↗