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PURPOSE: Differentiating pulmonary lymphoma from lung infections using CT images is challenging. Existing deep neural network-based lung CT classification models rely on 2D slices, lacking comprehensive information and requiring manual selection. 3D models that involve chunking compromise image information and struggle with parameter reduction, limiting performance. These limitations must be addressed to improve accuracy and practicality. METHODS: We propose a transformer sequential feature encoding structure to integrate multi-level information from complete CT images, inspired by the clinical practice of using a sequence of cross-sectional slices for diagnosis. We incorporate position encoding and cross-level long-range information fusion modules into the feature extraction CNN network for cross-sectional slices, ensuring high-precision feature extraction. RESULTS: We conducted comprehensive experiments on a dataset of 124 patients, with respective sizes of 64, 20 and 40 for training, validation and testing. The results of ablation experiments and comparative experiments demonstrated the effectiveness of our approach. Our method outperforms existing state-of-the-art methods in the 3D CT image classification problem of distinguishing between lung infections and pulmonary lymphoma, achieving an accuracy of 0.875, AUC of 0.953 and F1 score of 0.889. CONCLUSION: The experiments verified that our proposed position-enhanced transformer-based sequential feature encoding model is capable of effectively performing high-precision feature extraction and contextual feature fusion in the lungs. It enhances the ability of a standalone CNN network or transformer to extract features, thereby improving the classification performance. The source code is accessible at https://github.com/imchuyu/PTSFE .
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PURPOSE: Surgical action triplet recognition is a clinically significant yet challenging task. It provides surgeons with detailed information about surgical scenarios, thereby facilitating clinical decision-making. However, the high similarity among action triplets presents a formidable obstacle to recognition. To enhance accuracy, prior methods necessitated the utilization of larger models, thereby incurring a considerable computational burden. METHODS: We propose a novel framework known as the Lite and Mega Models (LAM). It comprises a CNN-based fully fine-tuned model (LAM-Lite) and a parameter-efficient fine-tuned model based on the foundation model using Transformer architecture (LAM-Mega). Temporal multi-label data augmentation is introduced for extracting robust class-level features. RESULTS: Our study demonstrates that LAM outperforms prior methods across various parameter scales on the CholecT50 dataset. Using fewer tunable parameters, LAM achieves a mean average precision (mAP) of 42.1%, a 3.6% improvement over the previous state of the art. CONCLUSION: Leveraging effective structural design and robust capabilities of the foundational model, our proposed approach successfully strikes a balance between accuracy and computational efficiency. The source code is accessible at https://github.com/Lycus99/LAM .
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Redes Neurales de la Computación , Humanos , Cirugía Asistida por Computador/métodos , Algoritmos , Toma de Decisiones Clínicas/métodosRESUMEN
Background: Surgical action recognition is an essential technology in context-aware-based autonomous surgery, whereas the accuracy is limited by clinical dataset scale. Leveraging surgical videos from virtual reality (VR) simulations to research algorithms for the clinical domain application, also known as domain adaptation, can effectively reduce the cost of data acquisition and annotation, and protect patient privacy. Methods: We introduced a surgical domain adaptation method based on the contrastive language-image pretraining model (SDA-CLIP) to recognize cross-domain surgical action. Specifically, we utilized the Vision Transformer (ViT) and Transformer to extract video and text embeddings, respectively. Text embedding was developed as a bridge between VR and clinical domains. Inter- and intra-modality loss functions were employed to enhance the consistency of embeddings of the same class. Further, we evaluated our method on the MICCAI 2020 EndoVis Challenge SurgVisDom dataset. Results: Our SDA-CLIP achieved a weighted F1-score of 65.9% (+18.9%) on the hard domain adaptation task (trained only with VR data) and 84.4% (+4.4%) on the soft domain adaptation task (trained with VR and clinical-like data), which outperformed the first place team of the challenge by a significant margin. Conclusions: The proposed SDA-CLIP model can effectively extract video scene information and textual semantic information, which greatly improves the performance of cross-domain surgical action recognition. The code is available at https://github.com/Lycus99/SDA-CLIP.
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Acute respiratory distress syndrome (ARDS) has a ~ 40% mortality rate with an increasing prevalence exacerbated by the COVID-19 pandemic. Mechanical ventilation is the primary means for life-saving support to buy time for lung healing in ARDS patients, however, it can also lead to ventilator-induced lung injury (VILI). Effective strategies to reduce or prevent VILI are necessary but are not currently delivered. Therefore, we aim at evaluating the current imaging technologies to visualize where pressure and volume being delivered to the lung during mechanical ventilation; and combining plasma biomarkers to guide management of mechanical ventilation. We searched PubMed and Medline using keywords and analyzed the literature, including both animal models and human studies, to examine the independent use of computed tomography (CT) to evaluate lung mechanics, electrical impedance tomography (EIT) to guide ventilation, ultrasound to monitor lung injury, and plasma biomarkers to indicate status of lung pathophysiology. This investigation has led to our proposal of the combination of imaging and biomarkers to precisely deliver mechanical ventilation to improve patient outcomes in ARDS.
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Despite similar infection rates, COVID-19 has resulted in more deaths in men than women. To understand the underlying mechanisms behind this sex-biased difference in disease severity, we infected K18-human angiotensin converting enzyme 2 (ACE2) mice of both sexes with SARS-CoV-2. Our study revealed a unique protein expression profile in the lung microenvironment of female mice. As a result, they were less vulnerable to severe infection, with higher ACE2 expression and a higher estrogen receptor α (ERα)/androgen receptor (AR) ratio that led to increased antiviral factor levels. In male mice, inhaling recombinant ACE2 neutralized the virus and maintained the ERα/AR ratio, thereby protecting the lungs. Our findings suggest that inhaling recombinant ACE2 could serve as a decoy receptor against SARS-CoV-2 and protect male mice by offsetting ERα-associated protective mechanisms. Additionally, our study supports the potential effectiveness of recombinant ACE2 therapy in human lung organoids infected with the Delta variant.
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The SARS-CoV-2 virus, implicated in the COVID-19 pandemic, recognizes and binds host cells using its spike glycoprotein through an angiotensin converting enzyme 2 (ACE-2) receptor-mediated pathway. Recent research suggests that spatial distributions of the spike protein may influence viral interactions with target cells and immune systems. The goal of this study has been to develop a liposome-based virus-like particle (VLP) by reconstituting the SARS-CoV-2 spike glycoprotein within a synthetic nanoparticle membrane, aiming to eventually establish tunability in spike protein presentation on the nanoparticle surface. Here we report on first steps to this goal, wherein liposomal SARS-CoV-2 VLPs were successfully produced via detergent mediated spike protein reconstitution. The resultant VLPs are shown to successfully co-localize in vitro with the ACE-2 receptor on lung epithelial cell surfaces, followed by internalization into these cells. These VLPs are the first step toward the overall goal of this research which is to form an understanding of the relationship between spike protein surface density and cell-level immune response, eventually toward creating better vaccines and anti-viral therapeutics.
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Surgical action triplet recognition plays a significant role in helping surgeons facilitate scene analysis and decision-making in computer-assisted surgeries. Compared to traditional context-aware tasks such as phase recognition, surgical action triplets, comprising the instrument, verb, and target, can offer more comprehensive and detailed information. However, current triplet recognition methods fall short in distinguishing the fine-grained subclasses and disregard temporal correlation in action triplets. In this article, we propose a multi-task fine-grained spatial-temporal framework for surgical action triplet recognition named MT-FiST. The proposed method utilizes a multi-label mutual channel loss, which consists of diversity and discriminative components. This loss function decouples global task features into class-aligned features, enabling the learning of more local details from the surgical scene. The proposed framework utilizes partial shared-parameters LSTM units to capture temporal correlations between adjacent frames. We conducted experiments on the CholecT50 dataset proposed in the MICCAI 2021 Surgical Action Triplet Recognition Challenge. Our framework is evaluated on the private test set of the challenge to ensure fair comparisons. Our model apparently outperformed state-of-the-art models in instrument, verb, target, and action triplet recognition tasks, with mAPs of 82.1% (+4.6%), 51.5% (+4.0%), 45.50% (+7.8%), and 35.8% (+3.1%), respectively. The proposed MT-FiST boosts the recognition of surgical action triplets in a context-aware surgical assistant system, further solving multi-task recognition by effective temporal aggregation and fine-grained features.
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Cirugía Asistida por Computador , HumanosRESUMEN
RATIONALE AND OBJECTIVES: The objective of this study is to accurately and timely assess the efficacy of patients with hepatocellular carcinoma (HCC) after the initial transarterial chemoembolization (TACE). MATERIALS AND METHODS: This retrospective study consisted of 279 patients with HCC in Center 1, who were split into training and validation cohorts in the ratio of 4:1, and 72 patients in Center 2 as an external testing cohort. Radiomics signatures both in the arterial phase and venous phase of contrast-enhanced computed tomography images were selected by univariate analysis, correlation analysis, and least absolute shrinkage and selection operator regression to build the predicting models. The clinical model and combined model were constructed by independent risk factors after univariate and multivariate logistic regression analysis. The biological interpretability of radiomics signatures correlating transcriptome sequencing data was explored using publicly available data sets. RESULTS: A total of 31 radiomics signatures in the arterial phase and 13 radiomics signatures in the venous phase were selected to construct Radscore_arterial and Radscore_venous, respectively, which were independent risk factors. After constructing the combined model, the area under the receiver operating characteristic curve in three cohorts was 0.865, 0.800, and 0.745, respectively. Through correlation analysis, 11 radiomics signatures in the arterial phase and 4 radiomics signatures in the venous phase were associated with 8 and 5 gene modules, respectively (All P < .05), which enriched some pathways closely related to tumor development and proliferation. CONCLUSION: Noninvasive imaging has considerable value in predicting the efficacy of patients with HCC after initial TACE. The biological interpretability of the radiological signatures can be mapped at the micro level.
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Carcinoma Hepatocelular , Quimioembolización Terapéutica , Neoplasias Hepáticas , Humanos , Carcinoma Hepatocelular/diagnóstico por imagen , Carcinoma Hepatocelular/terapia , Carcinoma Hepatocelular/patología , Neoplasias Hepáticas/diagnóstico por imagen , Neoplasias Hepáticas/terapia , Neoplasias Hepáticas/patología , Estudios Retrospectivos , Tomografía Computarizada por Rayos X/métodosRESUMEN
The COVID-19 pandemic caused by SARS-CoV-2 virus is an ongoing global health burden. Severe cases of COVID-19 and the rare cases of COVID-19 vaccine-induced-thrombotic-thrombocytopenia (VITT) are both associated with thrombosis and thrombocytopenia; however, the underlying mechanisms remain inadequately understood. Both infection and vaccination utilize the spike protein receptor-binding domain (RBD) of SARS-CoV-2. We found that intravenous injection of recombinant RBD caused significant platelet clearance in mice. Further investigation revealed the RBD could bind platelets, cause platelet activation, and potentiate platelet aggregation, which was exacerbated in the Delta and Kappa variants. The RBD-platelet interaction was partially dependent on the ß3 integrin as binding was significantly reduced in ß3-/- mice. Furthermore, RBD binding to human and mouse platelets was significantly reduced with related αIIbß3 antagonists and mutation of the RGD (arginine-glycine-aspartate) integrin binding motif to RGE (arginine-glycine-glutamate). We developed anti-RBD polyclonal and several monoclonal antibodies (mAbs) and identified 4F2 and 4H12 for their potent dual inhibition of RBD-induced platelet activation, aggregation, and clearance in vivo, and SARS-CoV-2 infection and replication in Vero E6 cells. Our data show that the RBD can bind platelets partially though αIIbß3 and induce platelet activation and clearance, which may contribute to thrombosis and thrombocytopenia observed in COVID-19 and VITT. Our newly developed mAbs 4F2 and 4H12 have potential not only for diagnosis of SARS-CoV-2 virus antigen but also importantly for therapy against COVID-19.
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Cases of vaccine breakthrough, especially in variants of concern (VOCs) infections, are emerging in coronavirus disease (COVID-19). Due to mutations of structural proteins (SPs) (e.g., Spike proteins), increased transmissibility and risk of escaping from vaccine-induced immunity have been reported amongst the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Remdesivir was the first to be granted emergency use authorization but showed little impact on survival in patients with severe COVID-19. Remdesivir is a prodrug of the nucleoside analogue GS-441524 which is converted into the active nucleotide triphosphate to disrupt viral genome of the conserved non-structural proteins (NSPs) and thus block viral replication. GS-441524 exerts a number of pharmacological advantages over Remdesivir: (1) it needs fewer conversions for bioactivation to nucleotide triphosphate; (2) it requires only nucleoside kinase, while Remdesivir requires several hepato-renal enzymes, for bioactivation; (3) it is a smaller molecule and has a potency for aerosol and oral administration; (4) it is less toxic allowing higher pulmonary concentrations; (5) it is easier to be synthesized. The current article will focus on the discussion of interactions between GS-441524 and NSPs of VOCs to suggest potential application of GS-441524 in breakthrough SARS-CoV-2 infections. Supplementary Information: The online version contains supplementary material available at 10.1007/s44231-022-00021-4.
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BACKGROUND: Large variability in mortality exists in patients of acute respiratory distress syndrome (ARDS), especially those with invasive ventilation. The aim of this study was to develop a model to predict risk of in-hospital death in ventilated ARDS patients. METHODS: Ventilated patients with ARDS from two public databases (MIMIC-III and eICU-CRD) were randomly divided as training cohort and internal validation cohort. Least absolute shrinkage and selection operator (LASSO) and then Logistic regression was used to construct a predictive model with demographic, clinical, laboratory, comorbidities and ventilation variables ascertained at first 24 h of ICU admission and invasive ventilation. Our model was externally validated using data from another database (MIMIC-IV). RESULTS: A total of 1075 adult patients from MIMIC-III and eICU were randomly divided into training cohort (70%, n = 752) and internal validation cohort (30%, n = 323). 521 patients were included from MIMIC-IV. From 176 potential predictors, 9 independent predictive factors were included in the final model. Five variables were ascertained within the first 24 h of ICU admission, including age (OR, 1.02; 95% CI: 1.01-1.03), mean of respiratory rate (OR, 1.04; 95% CI: 1.01-1.08), the maximum of INR (OR, 1.14; 95% CI: 1.03-1.31) and alveolo-arterial oxygen difference (OR, 1.002; 95% CI: 1.001-1.003) and the minimum of RDW (OR, 1.17; 95% CI: 1.09-1.27). And four variables were collected within the first 24 h of invasive ventilation: mean of temperature (OR, 0.70; 95% CI: 0.57-0.86), the maximum of lactate (OR, 1.15; 95% CI: 1.09-1.22), the minimum of blood urea nitrogen (OR, 1.02; 95% CI: 1.01-1.03) and white blood cell counts (OR, 1.03; 95% CI: 1.01-1.06). Our model achieved good discrimination (AUC: 0.77, 95% CI: 0.73-0.80) in training cohort but the performance declined in internal (AUC: 0.75, 95% CI: 0.69-0.80) and external validation cohort (0.70, 95% CI: 0.65-0.74) and showed modest calibration. CONCLUSIONS: A risk score based on routinely collected variables at the start of admission to ICU and invasive ventilation can predict mortality of ventilated ARDS patients, with a moderate performance.
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Respiración Artificial , Síndrome de Dificultad Respiratoria , Adulto , Estudios de Cohortes , Mortalidad Hospitalaria , Humanos , Modelos Logísticos , Síndrome de Dificultad Respiratoria/terapiaRESUMEN
BACKGROUND: Extubation to non-invasive ventilation (NIV) has been investigated as a strategy to wean critically ill adults from invasive ventilation and reduce ventilator-related complications. METHODS: We searched MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, proceedings of four conferences and bibliographies (to June 2020) for randomised and quasi-randomised trials that compared extubation with immediate application of NIV to continued invasive weaning in intubated adults and reported mortality (primary outcome) or other outcomes. Two reviewers independently screened citations, assessed trial quality and abstracted data. RESULTS: We identified 28 trials, of moderate-to-good quality, involving 2066 patients, 44.6% with chronic obstructive pulmonary disease (COPD). Non-invasive weaning significantly reduced mortality (risk ratio (RR) 0.57, 95% CI 0.44 to 0.74; high quality), weaning failures (RR 0.59, 95% CI 0.43 to 0.81; high quality), pneumonia (RR 0.30, 95% CI 0.22 to 0.41; high quality), intensive care unit (ICU) (mean difference (MD) -4.62 days, 95% CI -5.91 to -3.34) and hospital stay (MD -6.29 days, 95% CI -8.90 to -3.68). Non-invasive weaning also significantly reduced the total duration of ventilation, duration of invasive ventilation and duration of ventilation related to weaning (MD -0.57, 95% CI -1.08 to -0.07) and tracheostomy rate. Mortality, pneumonia, reintubation and ICU stay were significantly lower in trials enrolling COPD (vs mixed) populations. CONCLUSION: Non-invasive weaning significantly reduced mortality, pneumonia and the duration of ventilation related to weaning, particularly in patients with COPD. Beneficial effects are less clear (or more careful patient selection is required) in non-COPD patients. PROSPERO REGISTRATION NUMBER: CRD42020201402.
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Ventilación no Invasiva , Enfermedad Pulmonar Obstructiva Crónica , Adulto , Enfermedad Crítica/terapia , Humanos , Unidades de Cuidados Intensivos , Enfermedad Pulmonar Obstructiva Crónica/terapia , Respiración Artificial , Desconexión del VentiladorRESUMEN
The major variant of concerns (VOCs) have shared mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins, mostly on the S1 unit and resulted in higher transmissibility rate and affect viral virulence and clinical outcome. The spike protein mutations and other non-structural protein mutations in the VOCs may lead to escape approved vaccinations in certain extend. We will discuss these VOC mutations and discuss the need for combination therapeutic strategies targeting viral cycle and immune host responses.
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COVID-19/genética , SARS-CoV-2/aislamiento & purificación , Glicoproteína de la Espiga del Coronavirus/aislamiento & purificación , Vacunas contra la COVID-19 , Variación Genética , HumanosRESUMEN
G protein-coupled receptors (GPCRs) are the largest class of transmembrane proteins, making them an important target for therapeutics. Activation of these receptors is modulated by orthosteric ligands, which stabilize one or several states within a complex conformational ensemble. The intra- and inter-state dynamics, however, is not well documented. Here, we used single-molecule fluorescence to measure ligand-modulated conformational dynamics of the adenosine A2A receptor (A2AR) on nanosecond to millisecond timescales. Experiments were performed on detergent-purified A2R in either the ligand-free (apo) state, or when bound to an inverse, partial or full agonist ligand. Single-molecule Förster resonance energy transfer (smFRET) was performed on detergent-solubilized A2AR to resolve active and inactive states via the separation between transmembrane (TM) helices 4 and 6. The ligand-dependent changes of the smFRET distributions are consistent with conformational selection and with inter-state exchange lifetimes ≥ 3 ms. Local conformational dynamics around residue 2296.31 on TM6 was measured using fluorescence correlation spectroscopy (FCS), which captures dynamic quenching due to photoinduced electron transfer (PET) between a covalently-attached dye and proximal aromatic residues. Global analysis of PET-FCS data revealed fast (150-350 ns), intermediate (50-60 µs) and slow (200-300 µs) conformational dynamics in A2AR, with lifetimes and amplitudes modulated by ligands and a G-protein mimetic (mini-Gs). Most notably, the agonist binding and the coupling to mini-Gs accelerates and increases the relative contribution of the sub-microsecond phase. Molecular dynamics simulations identified three tyrosine residues (Y112, Y2887.53, and Y2907.55) as being responsible for the dynamic quenching observed by PET-FCS and revealed associated helical motions around residue 2296.31 on TM6. This study provides a quantitative description of conformational dynamics in A2AR and supports the idea that ligands bias not only GPCR conformations but also the dynamics within and between distinct conformational states of the receptor.
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Ligandos , Conformación Molecular , Simulación del Acoplamiento Molecular , Simulación de Dinámica Molecular , Receptor de Adenosina A2A/química , Receptor de Adenosina A2A/metabolismo , Algoritmos , Fluorescencia , Humanos , Modelos Teóricos , Imagen Molecular , Mutación , Unión Proteica , Imagen Individual de Molécula , Relación Estructura-ActividadRESUMEN
BACKGROUND: Neutrophil-to-lymphocyte count ratio (NLCR) has been shown as a feasible parameter associated with outcomes of tumor patients and an accessible predictor of bacteremia. However, only a handful of research shed the light on the association between NLCR and outcomes of septic patients. This study is aimed to evaluate the association between NLCR and all-cause mortality in a population of adult septic patients. METHODS: We extracted clinical data from Medical Information Mart for Intensive Care (MIMIC)-III V1.4, a free, large-scale, single-center database. NLCR was computed individually. Patients were categorized by quartiles of NLCR. The associations between NLCR quartiles and 28-day all-cause mortality in septic patients were assessed using Cox proportional hazards models and subgroup analyzes. To evaluate the accuracy of NLCR in predicting 28-day mortality of sepsis, receiver operator characteristic curves (ROC), areas under the curve (AUC), and the Youden's J Index were calculated. Other outcomes included 7-day all-cause mortality, mortality in the intensive care units (ICU), in-hospital mortality and length of ICU stay. RESULTS: A total of 3,043 eligible patients were included in the study, of which, 760, 759, 766 and 758 patients were fallen in the first quartile (≤5.89), the second quartile (>5.89, ≤10.69), the third quartile (>10.69, ≤20.25) and the fourth quartile (>20.25) of NLCR, respectively. The 7-day mortality (13.4%, 9.9%, 13.6% and 14.2%; P=0.064) showed no difference in the four quartiles. In multivariate analysis, after adjusting for confounding factors, the highest NLCR quartile (>20.25) was associated with increased 28-day all-cause mortality [hazard ratio (HR) 1.22, 95% Cl: 1.01-1.49; P=0.046]. The areas under the receiver operating characteristic curves (AUROCs) for NLCR was 0.553 (95% CI: 0.529-0.576) for 28-day mortality. CONCLUSIONS: High NLCR (>20.25) is independently related to increased 28-day all-cause mortality in adult septic patients of a limited sensibility and specificity. Further large multi-center prospective studies are needed to confirm such relationship and to validate whose clinical significance.
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More men than women have died from COVID-19. Genes encoded on X chromosomes, and sex hormones may explain the decreased fatality of COVID-19 in women. The angiotensin-converting enzyme 2 gene is located on X chromosomes. Men, with a single X chromosome, may lack the alternative mechanism for cellular protection after exposure to SARS-CoV-2. Some Toll-like receptors encoded on the X chromosomes can sense SARS-CoV-2 nucleic acids, leading to a stronger innate immunity response in women. Both estrogen and estrogen receptor-α contribute to T cell activation. Interventional approaches including estrogen-related compounds and androgen receptor antagonists may be considered in patients with COVID-19.
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Infecciones por Coronavirus/mortalidad , Disparidades en el Estado de Salud , Neumonía Viral/mortalidad , Caracteres Sexuales , COVID-19 , Femenino , Hormonas Esteroides Gonadales , Humanos , Inmunidad Innata , Masculino , Pandemias , Cromosomas Sexuales/genéticaRESUMEN
Counting fluorescence photobleaching steps is commonly used to infer the number n0 of monomeric units of individual oligomeric protein complexes or misfolded protein aggregates. We present a principled Bayesian approach for counting that incorporates the statistics of photobleaching. Our physics-based prior leads to a simple and efficient numerical scheme for maximum a posteriori probability (MAP) estimates of the initial fluorophore number n^0. Our focus here is on using a calibration to precisely estimate n^0, though our approach can also be used to calibrate the photophysics. Imaging noise increases with n^0, while bias is often introduced by temporal averaging. We examine the effects of fluorophore number n^0 of the oligomer or aggregate, lifetime photon yield µeff of an individual fluorophore, and exposure time Δt of each image frame in a time-lapse experiment. We find that, in comparison with standard ratiometric approaches or with a "change-point" step-counting algorithm, our MAP approach is both more precise and less biased.
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The original version of this Article contained errors in the author affiliations. Affiliation 2 incorrectly read 'Department of Biochemistry and Molecular Genetics and Breast Surgery, Ehime University Graduate School of Medicine, 7910295, Japan' and affiliation 3 incorrectly read 'Department of Hepato-Biliary-Pancreatic and Breast Surgery, Ehime University Graduate School of Medicine, Matsuyama 7910295, Japan.' These errors have now been corrected in both the PDF and HTML versions of the Article.
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The exocyst is a conserved octameric complex that tethers exocytic vesicles to the plasma membrane prior to fusion. Exocyst assembly and delivery mechanisms remain unclear, especially in mammalian cells. Here we tagged multiple endogenous exocyst subunits with sfGFP or Halo using Cas9 gene-editing, to create single and double knock-in lines of mammary epithelial cells, and interrogated exocyst dynamics by high-speed imaging and correlation spectroscopy. We discovered that mammalian exocyst is comprised of tetrameric subcomplexes that can associate independently with vesicles and plasma membrane and are in dynamic equilibrium with octamer and monomers. Membrane arrival times are similar for subunits and vesicles, but with a small delay (~80msec) between subcomplexes. Departure of SEC3 occurs prior to fusion, whereas other subunits depart just after fusion. About 9 exocyst complexes are associated per vesicle. These data reveal the mammalian exocyst as a remarkably dynamic two-part complex and provide important insights into assembly/disassembly mechanisms.
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Exocitosis , Complejos Multiproteicos/metabolismo , Vesículas Secretoras/metabolismo , Proteínas de Transporte Vesicular/metabolismo , Algoritmos , Animales , Línea Celular , Células Epiteliales/metabolismo , Femenino , Proteínas Fluorescentes Verdes/genética , Proteínas Fluorescentes Verdes/metabolismo , Células HEK293 , Humanos , Glándulas Mamarias Animales/citología , Fusión de Membrana , Ratones , Microscopía Confocal , Modelos Biológicos , Complejos Multiproteicos/genética , Transporte de Proteínas , Proteínas de Transporte Vesicular/genéticaRESUMEN
Uncertainty over the mechanism of signaling via G protein-coupled receptors (GPCRs) relates in part to questions regarding their supramolecular structure. GPCRs and heterotrimeric G proteins are known to couple as monomers under various conditions. Many GPCRs form oligomers under many of the same conditions, however, and the biological role of those complexes is unclear. We have used dual-color fluorescence correlation spectroscopy to identify oligomers of the M2 muscarinic receptor and of Gi1 in purified preparations and live Chinese hamster ovary cells. Measurements on differently tagged receptors (i.e., eGFP-M2 and mCherry-M2) and G proteins (i.e., eGFP-Gαi1ß1γ2 and mCherry-Gαi1ß1γ2) detected significant cross-correlations between the two fluorophores in each case, both in detergent micelles and in live cells, indicating that both the receptor and Gi1 can exist as homo-oligomers. Oligomerization of differently tagged Gi1 decreased upon the activation of co-expressed wild-type M2 receptor by an agonist. Measurements on a tagged M2 receptor (M2-mCherry) and eGFP-Gαi1ß1γ2 co-expressed in live cells detected cross-correlations only in the presence of an agonist, which therefore promoted coupling of the receptor and the G protein. The effect of the agonist was retained when a fluorophore-tagged receptor lacking the orthosteric site (i.e., M2(D103A)-mCherry) was co-expressed with the wild-type receptor and eGFP-Gαi1ß1γ2, indicating that the ligand acted via an oligomeric receptor. Our results point to a model in which an agonist promotes transient coupling of otherwise independent oligomers of the M2 receptor on the one hand and of Gi1 on the other and that an activated complex leads to a reduction in the oligomeric size of the G protein. They suggest that GPCR-mediated signaling proceeds, at least in part, via oligomers.