The endosomal sorting complex required for transport (ESCRT) machinery is an ancient system that deforms membrane and severs membrane necks from the inside. Extensive evidence has accumulated to ...demonstrate the conserved functions of plant ESCRTs in multivesicular body (MVB) biogenesis and MVB-mediated membrane protein sorting. In addition, recent exciting findings have uncovered unique plant ESCRT components and point to emerging roles for plant ESCRTs in non-endosomal sorting events such as autophagy, cytokinesis, and viral replication. Plant-specific processes, such as abscisic acid (ABA) signaling and chloroplast turnover, provide further evidence for divergences in the functions of plant ESCRTs during evolution. We summarize the multiple roles and current working models for plant ESCRT machinery and speculate on future ESCRT studies in the plant field.
ESCRT is an evolutionarily conserved machinery for membrane deformation and scission from the inner face of a membrane away from the cytoplasm.
Plants encode most ESCRT isoforms in their genome, including ESCRT-I, -II, -III, and VPS4/SKD1, with the exception of the canonical ESCRT-0. TOL (TOM1-like) proteins were identified as upstream ESCRT factors that partially fulfill ESCRT-0 function in plants.
Extensive evidence has accumulated to demonstrate the essential and conserved functions of ESCRTs in endosomal sorting in plants.
Plant-specific ESCRT components have been identified. In addition, ESCRTs in plants are also involved in a variety of non-endosomal sorting events such as autophagosome maturation, chloroplast turnover, cytokinesis, and viral replication.
Plant ESCRTs are also actively involved in hormone signaling and plant responses to biotic and abiotic stresses.
Identifying olive cultivars and maturity stages is crucial in the olive industry, as these traits significantly impact the nutritional and sensory properties of olive products and extracted oil. For ...this purpose, this study presents a novel automatic computer vision system that applies state-of-the-art deep learning technology to sort and classify two Iranian olive cultivars, Zard and Roghani, in five maturity stages, resulting in a total of ten distinct classes. The model was developed by evaluating multiple user-defined and standard structures. It was based on a dual-path lightweight convolutional neural network that uses both regular and dilated convolution operators. Dilated convolutions were used to extract more information and capture different properties by providing larger receptive fields. With a significantly lower number of trainable parameters than standard architectures, the lightweight nature of the model would enhance its potential for delivering fast responses in on-the-go applications. Four optimizers (RMSProp, SGD, Adam, and Nadam) were tested on the developed model to enhance its performance, and Nadam exhibited the greatest accuracy. The proposed model achieved a total classification accuracy of 95.79 % and a loss of 0.2214. The proposed model was completely accurate for some classes, and the classification metrics for all categories were high, ranging from 88 % to 100 % for precision, 83–100 % for recall, and 86–100 % for F1-score. The accuracy of classification within the Roghani cultivar classes stood at 98.28 %, while for the Zard cultivar classes, it achieved 97.76 %. The study found that the proposed model can be efficiently incorporated into an olive sorting system, facilitating the identification of olives with different cultivars and varying levels of maturity, thereby enhancing the production of post-harvest products and superior quality of oil.
•RGB images and DL were used to sort two olive cultivars in five maturity stages.•Dual-path lightweight CNN with both regular and dilated convolutions was employed.•Four optimizers were tested on the developed model to enhance its performance.•Promising results in terms of classification metrics were achieved.
Sorting machines use computer vision (CV) to separate food items based on various attributes. For instance, sorting based on size and colour are commonly used in commercial machines. However, ...detecting external defects using CV remains an open problem. This paper presents an experimental contribution to external defect detection using deep learning. An uncensored dataset with 43,843 images including external defects was built during this study. The dataset is heavily imbalanced towards the healthy class, and it is available online. Deep residual neural network (ResNet) classifiers were trained that are capable of detecting external defects using feature extraction and fine-tuning. The results show that fine-tuning outperformed feature extraction, revealing the benefit of training additional layers when sufficient data samples are available. The best model was a ResNet50 with all its layers fine-tuned. This model achieved an average precision of 94.6% on the test set. The optimal classifier had a recall of 86.6% while maintaining a precision of 91.7%. The posterior class-conditional distributions of the classifier scores showed that the key to classifier success lies in its almost ideal healthy class distribution. The results also explain why the model does not confuse stems/calyxes with external defects. The best model constitutes a milestone for detecting external defects using CV. Because deep learning does not require feature engineering or prior knowledge about the dataset content, the methodology may also work well with other foods.
•Deep learning detects different types of external defects without feature engineering.•Fine tuning outperformed feature extraction in external defect detection.•The best model has Average Precision = 94.6 %.•The best model has 86.6 % Recall and 91.7 % Precision at the optimal threshold.•The best model does not confuse external defects with stems/calyxes.
Phosphatidylinositol 3-kinase Vps34 complexes regulate intracellular membrane trafficking in endocytic sorting, cytokinesis, and autophagy. We present the 4.4 angstrom crystal structure of the ...385-kilodalton endosomal complex II (PIK3C3-CII), consisting of Vps34, Vps15 (p150), Vps30/Atg6 (Beclin 1), and Vps38 (UVRAG). The subunits form a Y-shaped complex, centered on the Vps34 C2 domain. Vps34 and Vps15 intertwine in one arm, where the Vps15 kinase domain engages the Vps34 activation loop to regulate its activity. Vps30 and Vps38 form the other arm that brackets the Vps15/Vps34 heterodimer, suggesting a path for complex assembly. We used hydrogen-deuterium exchange mass spectrometry (HDX-MS) to reveal conformational changes accompanying membrane binding and identify a Vps30 loop that is critical for the ability of complex II to phosphorylate giant liposomes on which complex I is inactive.
Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from ...amino acid sequences, but most cannot distinguish between various types of signal peptides. We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs.
Exosomes transport a variety of macromolecules and modulate intercellular communication in physiology and disease. However, the regulation mechanisms that determine exosome contents during exosome ...biogenesis remain poorly understood. Here, we find that GPR143, an atypical GPCR, controls the endosomal sorting complex required for the transport (ESCRT)-dependent exosome biogenesis pathway. GPR143 interacts with HRS (an ESCRT-0 Subunit) and promotes its association to cargo proteins, such as EGFR, which subsequently enables selective protein sorting into intraluminal vesicles (ILVs) in multivesicular bodies (MVBs). GPR143 is elevated in multiple cancers, and quantitative proteomic and RNA profiling of exosomes in human cancer cell lines showed that the GPR143-ESCRT pathway promotes secretion of exosomes that carry unique cargo, including integrins signaling proteins. Through gain- and loss-of-function studies in mice, we show that GPR143 promotes metastasis by secreting exosomes and increasing cancer cell motility/invasion through the integrin/FAK/Src pathway. These findings provide a mechanism for regulating the exosomal proteome and demonstrate its ability to promote cancer cell motility.
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•GPR143 regulates ESCRT-dependent exosome production•GPR143 recruits HRS to endosomes to modulate interaction with cargo protein•GPR143 regulates protein sorting in ILVs and alters exosomal proteome composition•Exosomal integrins activate the cell motility signaling pathway to promote metastasis
Lee et al. find that GPR143, an atypical GPCR, controls the ESCRT-dependent exosome biogenesis pathway, which determines exosomal protein cargo composition. In cancer, GPR143 expression facilitates secretion of oncogenic exosomes, which contain integrins that promote cell motility and cancer metastasis.
The current literature of evolutionary many-objective optimization is merely focused on the scalability to the number of objectives, while little work has considered the scalability to the number of ...decision variables. Nevertheless, many real-world problems can involve both many objectives and large-scale decision variables. To tackle such large-scale many-objective optimization problems (MaOPs), this paper proposes a specially tailored evolutionary algorithm based on a decision variable clustering method. To begin with, the decision variable clustering method divides the decision variables into two types: 1) convergence-related variables and 2) diversity-related variables. Afterward, to optimize the two types of decision variables, a convergence optimization strategy and a diversity optimization strategy are adopted. In addition, a fast nondominated sorting approach is developed to further improve the computational efficiency of the proposed algorithm. To assess the performance of the proposed algorithm, empirical experiments have been conducted on a variety of large-scale MaOPs with up to ten objectives and 5000 decision variables. Our experimental results demonstrate that the proposed algorithm has significant advantages over several state-of-the-art evolutionary algorithms in terms of the scalability to decision variables on MaOPs.
The ESCRT machinery Schmidt, Oliver; Teis, David
Current biology,
02/2012, Letnik:
22, Številka:
4
Journal Article
Recenzirano
Odprti dostop
The endosomal sorting complexes required for transport (ESCRT) assemble into a multisubunit machinery that performs a topologically unique membrane bending and scission reaction away from the ...cytoplasm. This evolutionarily highly conserved process is required for the multivesicular body (MVB) pathway, cytokinesis and HIV budding. The modular setup of the machinery with five distinct ESCRT complexes (ESCRT-0, -I, -II, -III and the Vps4 complex) that have a clear division of tasks — from interaction with ubiquitinated membrane proteins to membrane deformation and abscission — allows them to be flexibly integrated into these three very different biological processes (Figure 1).
HIV-1 infection causes AIDS, infecting millions worldwide. The virus can persist in a state of chronic infection due to its ability to become latent. We have previously shown a link between HIV-1 ...infection and exosome production. Specifically, we have reported that exosomes transport viral proteins and RNA from infected cells to neighboring uninfected cells. These viral products could then elicit an innate immune response, leading to activation of the Toll-like receptor and NF-κB pathways. In this study, we asked whether exosomes from uninfected cells could activate latent HIV-1 in infected cells. We observed that irrespective of combination antiretroviral therapy, both short- and long-length viral transcripts were increased in wild-type HIV-1–infected cells exposed to purified exosomes from uninfected cells. A search for a possible mechanism for this finding revealed that the exosomes increase RNA polymerase II loading onto the HIV-1 promoter in the infected cells. These viral transcripts, which include trans-activation response (TAR) RNA and a novel RNA that we termed TAR-gag, can then be packaged into exosomes and potentially be exported to neighboring uninfected cells, leading to increased cellular activation. To better decipher the exosome release pathways involved, we used siRNA to suppress expression of ESCRT (endosomal sorting complex required for transport) proteins and found that ESCRT II and IV significantly control exosome release. Collectively, these results imply that exosomes from uninfected cells activate latent HIV-1 in infected cells and that true transcriptional latency may not be possible in vivo, especially in the presence of combination antiretroviral therapy.
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