Cryo-EM structures of membrane-bound dynamin in a post-hydrolysis state primed for membrane fission.

Dynamin assembles as a helical polymer at the neck of budding endocytic vesicles, constricting the underlying membrane as it progresses through the GTPase cycle to sever vesicles from the plasma membrane. Although atomic models of the dynamin helical polymer bound to guanosine triphosphate (GTP) analogs define earlier stages of membrane constriction, there are no atomic models of the assembled state post-GTP hydrolysis. Here, we used cryo-EM methods to determine atomic structures of the dynamin helical polymer assembled on lipid tubules, akin to necks of budding endocytic vesicles, in a guanosine diphosphate (GDP)-bound, super-constricted state. In this state, dynamin is assembled as a 2-start helix with an inner lumen of 3.4 nm, primed for spontaneous fission. Additionally, by cryo-electron tomography, we trapped dynamin helical assemblies within HeLa cells using the GTPase-defective dynamin K44A mutant and observed diverse dynamin helices, demonstrating that dynamin can accommodate a range of assembled complexes in cells that likely precede membrane fission.

Role of Internet of Things and Deep Learning Techniques in Plant Disease Detection and Classification: A Focused Review.

The automatic detection, visualization, and classification of plant diseases through image datasets are key challenges for precision and smart farming. The technological solutions proposed so far highlight the supremacy of the Internet of Things in data collection, storage, and communication, and deep learning models in automatic feature extraction and feature selection. Therefore, the integration of these technologies is emerging as a key tool for the monitoring, data capturing, prediction, detection, visualization, and classification of plant diseases from crop images. This manuscript presents a rigorous review of the Internet of Things and deep learning models employed for plant disease monitoring and classification. The review encompasses the unique strengths and limitations of different architectures. It highlights the research gaps identified from the related works proposed in the literature. It also presents a comparison of the performance of different deep learning models on publicly available datasets. The comparison gives insights into the selection of the optimum deep learning models according to the size of the dataset, expected response time, and resources available for computation and storage. This review is important in terms of developing optimized and hybrid models for plant disease classification.

Structural insights into thermostable direct hemolysin of Vibrio parahaemolyticus using single-particle cryo-EM.

Thermostable direct hemolysin (TDH) is a ~19 kDa, hemolytic pore-forming toxin from the gram-negative marine bacterium Vibrio parahaemolyticus, one of the causative agents of seafood-borne acute gastroenteritis and septicemia. Previous studies have established that TDH exists as a tetrameric assembly in physiological state; however, there is limited knowledge regarding the molecular arrangement of its disordered N-terminal region (NTR)-the absence of which has been shown to compromise TDH's hemolytic and cytotoxic abilities. In our current study, we have employed single-particle cryo-electron microscopy to resolve the solution-state structures of wild-type TDH and a TDH construct with deletion of the NTR (NTD), in order to investigate structural aspects of NTR on the overall tetrameric architecture. We observed that both TDH and NTD electron density maps, resolved at global resolutions of 4.5 and 4.2 Å, respectively, showed good correlation in their respective oligomeric architecture. Additionally, we were able to locate extra densities near the pore opening of TDH which might correspond to the disordered NTR. Surprisingly, under cryogenic conditions, we were also able to observe novel supramolecular assemblies of TDH tetramers, which we were able to resolve to 4.3 Å. We further investigated the tetrameric and inter-tetrameric interaction interfaces to elaborate upon the key residues involved in both TDH tetramers and TDH super assemblies. Our current structural study will aid in understanding the mechanistic aspects of this pore-forming toxin and the role of its disordered NTR in membrane interaction.

Molecular mechanics underlying flat-to-round membrane budding in live secretory cells.

Membrane budding entails forces to transform flat membrane into vesicles essential for cell survival. Accumulated studies have identified coat-proteins (e.g., clathrin) as potential budding factors. However, forces mediating many non-coated membrane buddings remain unclear. By visualizing proteins in mediating endocytic budding in live neuroendocrine cells, performing in vitro protein reconstitution and physical modeling, we discovered how non-coated-membrane budding is mediated: actin filaments and dynamin generate a pulling force transforming flat membrane into Λ-shape; subsequently, dynamin helices surround and constrict Λ-profile's base, transforming Λ- to Ω-profile, and then constrict Ω-profile's pore, converting Ω-profiles to vesicles. These mechanisms control budding speed, vesicle size and number, generating diverse endocytic modes differing in these parameters. Their impact is widespread beyond secretory cells, as the unexpectedly powerful functions of dynamin and actin, previously thought to mediate fission and overcome tension, respectively, may contribute to many dynamin/actin-dependent non-coated-membrane buddings, coated-membrane buddings, and other membrane remodeling processes.

IoT and Interpretable Machine Learning Based Framework for Disease Prediction in Pearl Millet.

Decrease in crop yield and degradation in product quality due to plant diseases such as rust and blast in pearl millet is the cause of concern for farmers and the agriculture industry. The stipulation of expert advice for disease identification is also a challenge for the farmers. The traditional techniques adopted for plant disease detection require more human intervention, are unhandy for farmers, and have a high cost of deployment, operation, and maintenance. Therefore, there is a requirement for automating plant disease detection and classification. Deep learning and IoT-based solutions are proposed in the literature for plant disease detection and classification. However, there is a huge scope to develop low-cost systems by integrating these techniques for data collection, feature visualization, and disease detection. This research aims to develop the 'Automatic and Intelligent Data Collector and Classifier' framework by integrating IoT and deep learning. The framework automatically collects the imagery and parametric data from the pearl millet farmland at ICAR, Mysore, India. It automatically sends the collected data to the cloud server and the Raspberry Pi. The 'Custom-Net' model designed as a part of this research is deployed on the cloud server. It collaborates with the Raspberry Pi to precisely predict the blast and rust diseases in pearl millet. Moreover, the Grad-CAM is employed to visualize the features extracted by the 'Custom-Net'. Furthermore, the impact of transfer learning on the 'Custom-Net' and state-of-the-art models viz. Inception ResNet-V2, Inception-V3, ResNet-50, VGG-16, and VGG-19 is shown in this manuscript. Based on the experimental results, and features visualization by Grad-CAM, it is observed that the 'Custom-Net' extracts the relevant features and the transfer learning improves the extraction of relevant features. Additionally, the 'Custom-Net' model reports a classification accuracy of 98.78% that is equivalent to state-of-the-art models viz. Inception ResNet-V2, Inception-V3, ResNet-50, VGG-16, and VGG-19. Although the classification of 'Custom-Net' is comparable to state-of-the-art models, it is effective in reducing the training time by 86.67%. It makes the model more suitable for automating disease detection. This proves that the proposed model is effective in providing a low-cost and handy tool for farmers to improve crop yield and product quality.

Time-resolved cryo-EM using Spotiton.

We present an approach for preparing cryo-electron microscopy (cryo-EM) grids to study short-lived molecular states. Using piezoelectric dispensing, two independent streams of ~50-pl droplets of sample are deposited within 10 ms of each other onto the surface of a nanowire EM grid, and the mixing reaction stops when the grid is vitrified in liquid ethane ~100 ms later. We demonstrate this approach for four biological systems where short-lived states are of high interest.

N-Terminal Region of Vibrio parahemolyticus Thermostable Direct Hemolysin Regulates the Membrane-Damaging Action of the Toxin.

Thermostable direct hemolysin (TDH) of Vibrio parahemolyticus is a membrane-damaging pore-forming toxin with potent cytolytic/cytotoxic activity. TDH exists as a tetramer consisting of protomers with a core ß-sandwich domain, flanked by an 11-amino acid long N-terminal region (NTR). This NTR could not be modeled in the previously determined crystal structure of TDH. Moreover, the functional implication of NTR for the membrane-damaging action of TDH remains unknown. In the present study, we have explored the implications of NTR for the structure-function mechanism of TDH. Our data show that the presence of NTR modulates the physicochemical property of TDH in terms of augmenting the amyloidogenic propensity of the protein. Deletion of NTR compromises the binding of TDH toward target cell membranes and drastically affects the membrane-damaging cytolytic/cytotoxic activity of the toxin. Mutations of aromatic/hydrophobic residues within NTR also confer compromised cell-killing activity. Moreover, covalent trapping of NTR, via an engineered disulfide bond, against the core ß-sandwich domain also abrogates the cytolytic/cytotoxic activity of TDH. This observation suggests that an unrestrained configuration of NTR is crucial for the membrane-damaging action of TDH. On the basis of our study, we propose a model explaining the role of NTR in the membrane-damaging function of TDH.

Structural Basis and Functional Implications of the Membrane Pore-Formation Mechanisms of Bacterial Pore-Forming Toxins.

Pore-forming toxins (PFTs) are a distinct class of membrane-damaging protein toxins documented in a wide array of life forms ranging from bacteria to humans. PFTs are known to act as potent virulence factors of the bacterial pathogens. Bacterial PFTs are, in general, secreted as water-soluble molecules, which upon encountering target host cells assemble into transmembrane oligomeric pores, thus leading to membrane permeabilization and cell death. Interaction of the PFTs with the target host cells can also lead to plethora of cellular responses having critical implications for the bacterial pathogenesis processes, host-pathogen interactions, and host immunity. In this review, we present an overview of our current understanding of the structural aspects of the membrane pore-formation processes employed by the bacterial PFTs. We also discuss the functional implications of the PFT mode of actions, in terms of eliciting diverse cellular responses.

Disulphide bond restrains the C-terminal region of thermostable direct hemolysin during folding to promote oligomerization.

Pore-forming toxins (PFTs) are typically produced as water-soluble monomers, which upon interacting with target cells assemble into transmembrane oligomeric pores. Vibrio parahaemolyticus thermostable direct hemolysin (TDH) is an atypical PFT that exists as a tetramer in solution, prior to membrane binding. The TDH structure highlights a core ß-sandwich domain similar to those found in the eukaryotic actinoporin family of PFTs. However, the TDH structure harbors an extended C-terminal region (CTR) that is not documented in the actinoporins. This CTR remains tethered to the ß-sandwich domain through an intra-molecular disulphide bond. Part of the CTR is positioned at the inter-protomer interface in the TDH tetramer. Here we show that the truncation, as well as mutation, of the CTR compromise tetrameric assembly, and the membrane-damaging activity of TDH. Our study also reveals that intra-protomer disulphide bond formation during the folding/assembly process of TDH restrains the CTR to mediate its participation in the formation of inter-protomer contact, thus facilitating TDH oligomerization. However, once tetramerization is achieved, disruption of the disulphide bond does not affect oligomeric assembly. Our study provides critical insights regarding the regulation of the oligomerization mechanism of TDH, which has not been previously documented in the PFT family.

Physicochemical constraints of elevated pH affect efficient membrane interaction and arrest an abortive membrane-bound oligomeric intermediate of the beta-barrel pore-forming toxin Vibrio cholerae cytolysin.

Vibrio cholerae cytolysin (VCC) is a potent membrane-damaging cytotoxic protein. VCC causes permeabilization of the target cell membranes by forming transmembrane oligomeric beta-barrel pores. Membrane pore formation by VCC involves following key steps: (i) membrane binding, (ii) formation of a pre-pore oligomeric intermediate, (iii) membrane insertion of the pore-forming motifs, and (iv) formation of the functional transmembrane pore. Membrane binding, oligomerization, and subsequent pore-formation process of VCC appear to be facilitated by multiple regulatory mechanisms that are only partly understood. Here, we have explored the role(s) of the physicochemical constraints, specifically imposed by the elevated pH conditions, on the membrane pore-formation mechanism of VCC. Elevated pH abrogates efficient interaction of VCC with the target membranes, and blocks its pore-forming activity. Under the elevated pH conditions, membrane-bound fractions of VCC remain trapped in the form of abortive oligomeric species that fail to generate the functional transmembrane pores. Such an abortive oligomeric assembly appears to represent a distinct, more advanced intermediate state than the pre-pore state. The present study offers critical insights regarding the implications of the physicochemical constraints for regulating the efficient membrane interaction and pore formation by VCC.

Preparation and characterization of glucose oxidase nanoparticles and their application in dissolved oxygen metric determination of serum glucose.

The nanoparticle (NP) aggregates of commercial glucose oxidase (GOD) from A. niger with 117 nm diameter, were prepared by desolvation method. The formation and characterization of GOD-NP aggregates was studied by UV, transmission electron microscopic (TEM) and Fourier transform infrared (FTIR) spectra. GOD-NP aggregates were more stable, active and had a higher shelf life than that of free enzyme. These GOD-NP aggregates were immobilized onto chitosan activated nitrocellulose (NC) membrane through glutaraldehyde coupling with 55.15% retention of initial activity of free enzyme and 5.9 microg protein/cm2 yield. The membrane bound GOD-NP aggregates showed optimum response within 60 s, at pH 6.0, temperature range 30-45 degrees C with a peak at 35 degrees C and a hyperbolic relationship with glucose upto 250 mg/dl. Apparent K(m) and V(max) were 75 mg/dl and 0.06 mg/l respectively. The NC membrane bound GOD-NP aggregates were employed for dissolved O2 (DO) metric determination of serum glucose in apparently healthy and diabetic adults. The present method of serum glucose determination was evaluated.