Biology subjects

Chowdhury, R.

Publications and source records attributed to Chowdhury, R..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Arms race of physical defences: Hooked trichomes of Macaranga ant-plants kill lycaenid caterpillars, but one specialist has a counter-defence

The co-evolution of insects and chemical plant defences has been described as an arms-race, but it is unclear if physical plant defences can produce similar outcomes. Here we report a previously unknown interaction from the mutualism between ants and Macaranga trees. Although Macaranga trees are well protected against herbivory by aggressive ants, caterpillars of the genus Arhopala (Lepidoptera: Lycaenidae) can feed on the leaves by appeasing the ants with nectar-like secretions. One ant-plant species, M. trachyphylla, bears hooked trichomes on its green surfaces. When placed on M. trachyphylla stems or petioles, Arhopala caterpillars associated with other Macaranga species (A. major, A. dajagaka and A. zylda) were quickly arrested by the sharp trichomes which pierced their cuticle, resulting in rapid loss of blood and death. In striking contrast, A. amphimuta caterpillars, which occur naturally on M. trachyphylla, could easily walk over the hooked trichomes without any injury. As hooked trichomes are a novel trait within Macaranga, this interaction provides an example of de novo evolution of a physical plant defence, which in turn has been overcome by a specialist herbivore. Our study suggests that physical plant defences can lead to evolutionary arms races similar to those for chemical defences.

zoology↗

bioRxiv2025

Improved Functional Classification of Hydrolases through Pairwise Structural Similarity of Reaction Cores

We report a systematic pipeline is for extracting the catalytically relevant reactive site in addition to the surrounding allosterically linked residue shells around the reaction site of the most diverse enzyme class - hydrolases, with known experimental structures. We first successfully extract 40196 such hydrolase reaction cores (RC) and collates them into a publicly accessible reaction core collection (RC-Hydrolase). We perform 128M pairwise shape comparison across RC-Hydrolase using a three-dimensional search engine and present 155,329 pair instances clustering them by 60% or higher similarities in a publicly available, visually interactive dataset. Robustness of defined RCs is shown to successfully capture experimentally known function-enhancing mutations distal to the active site in PETases. Allowing comparisons of enzyme reaction centers across functional spaces (ligands bound, EC classification numbers, and expression hosts) enables identification of enzyme backbones which can be minimally mutated to accommodate more than one type of catalytic activity thereby aiding rational design of multifunctional enzymes. We also demonstrate how such versatile enzyme backbones could be leveraged by the latest diffusion-based protein design models to design bespoke libraries of small molecule inhibitors, and structurally stable multifunctional enzyme pockets. With only sporadic successes in multifunctional enzyme design thus far, we provide strong structural priors for machine-learning-guided advanced enzyme engineering in the future.

bioinformatics↗

bioRxiv2024

Exploring putative enteric methanogenesis inhibitors using molecular simulations and a graph neural network

Atmospheric methane (CH4) acts as a key contributor to global warming. As CH4 is a short-lived climate forcer (12 years atmospheric lifespan), its mitigation represents the most promising means to address climate change in the short term. Enteric CH4 (the biosynthesized CH4 from the rumen of ruminants) represents 5.1% of total global greenhouse gas (GHG) emissions, 23% of emissions from agriculture, and 27.2% of global CH4 emissions. Therefore, it is imperative to investigate methanogenesis inhibitors and their underlying modes of action. We hereby elucidate the detailed biophysical and thermodynamic interplay between anti-methanogenic molecules and cofactor F430 of methyl coenzyme M reductase and interpret the stoichiometric ratios and binding affinities of sixteen inhibitor molecules. We leverage this as prior in a graph neural network to first functionally cluster these sixteen known inhibitors among [~]54,000 bovine metabolites. We subsequently demonstrate a protocol to identify precursors to and putative inhibitors for methanogenesis, based on Tanimoto chemical similarity and membrane permeability predictions. This work lays the foundation for computational and de novo design of inhibitor molecules that retain/ reject one or more biochemical properties of known inhibitors discussed in this study. COVER ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/613350v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1fd4518org.highwire.dtl.DTLVardef@c34d87org.highwire.dtl.DTLVardef@16eef9org.highwire.dtl.DTLVardef@1a33512_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2024

Nanobodies against the myelin enzyme CNPase as tools for structural and functional studies

2,3-cyclic nucleotide 3-phosphodiesterase (CNPase) is an abundant constituent of central nervous system non-compact myelin, frequently used as a marker antigen for myelinating cells. The catalytic activity of CNPase, the 3-hydrolysis of 2,3-cyclic nucleotides, is well characterised in vitro, but the in vivo function of CNPase remains unclear. CNPase interacts with the actin cytoskeleton to counteract the developmental closure of cytoplasmic channels that travel through compact myelin; its enzymatic activity may be involved in adenosine metabolism and RNA degradation. We developed a set of high-affinity nanobodies recognizing the phosphodiesterase domain of CNPase, and the crystal structures of each complex show that the five nanobodies have distinct epitopes. One of the nanobodies bound deep into the CNPase active site and acted as an inhibitor. Moreover, the nanobodies were characterised in imaging applications and as intrabodies, expressed in mammalian cells, such as primary oligodendrocytes. Fluorescently labelled nanobodies functioned in imaging of teased nerve fibers and whole brain tissue sections, as well as super-resolution microscopy. These anti-CNPase nanobodies provide new tools for structural and functional biology of myelination, including high-resolution imaging of nerve tissue.

biochemistry↗

bioRxiv2024

Chloroquine attenuates hypoxia-mediated autophagy to curb thrombosis- an ex vivo and in vivo study

BackgroundHypoxia can trigger the activation of blood platelets, leading to thrombosis. If not addressed clinically, it can cause severe complications and fatal consequences as well. The current treatment regime for thrombosis is often palliative and includes long-term administration of anticoagulants, which has the risk of over-bleeding in injury and other secondary effects as well. This demands a deeper understanding of the process and exploration of an alternative therapeutic avenue. Interestingly, recent studies demonstrate that platelets though atypical and enucleated, possess components of autophagy machinery. This cellular homeostatic process though well-studied in non-platelet cells, is under-explored in platelets. MethodsIn this study, we report an activation of autophagy in rat-derived platelets cultured under physiologically relevant hypoxic condition (10% O2) ex vivo. Furthermore, autophagy was triggered in vivo when rats were exposed to hypobaric hypoxic conditions. Subsequently, restriction or surgical ligation of the inferior vena cava (IVC) was performed to induce thrombus formation. Post confirming the impact of autophagy induction on platelet functioning, it was inhibited, and then platelet activation and aggregation status were evaluated using light transmission aggregometry, flow cytometry, immunofluorescence and immunoblotting. ResultsHerein, we show that autophagy inhibition with the potent autophagy inhibitor-CQ, a repurposed FDA-approved drug, can significantly reduce platelet activation, both in ex vivo and in vivo settings. CQ withdrawal reversed the phenomenon indicating a dynamic effect. Thereafter, in flow restriction or surgical ligation model, interestingly, CQ-pre-treated rats showed reduced clotting ability. Importantly, CQ at the stipulated dose was found to be non-toxic to the tissues, as analyzed through histological staining. ConclusionThus, we propose that the repurpose of the FDA approved drug CQ can attenuate hypoxia-induced thrombosis through inhibition of autophagy and can be explored as an effective therapeutic alternative. HighlightsO_LIExposure of ex-vivo cultured platelets to physiologically relevant hypoxic condition (O2 concentration) can induce autophagy causing them to get activated and eventually aggregate. C_LIO_LIFDA approved drug chloroquine (CQ) is able to inhibit autophagy in anucleate cellular fragments, platelets, similar to nucleated cells and curb platelet functioning under hypoxic condition in both ex-vivo and in-vivo model. C_LIO_LIFlow restriction model mimicking deep vein thrombosis, emphasizes on the effect of CQ on impeding thrombus formation when used at a non-toxic dosage. C_LI

physiology↗

bioRxiv2023

Dissecting Metabolic Landscape of Alveolar Macrophage

The highly plastic nature of Alveolar Macrophage (AM) plays a crucial role in the defense against inhaled particulates and pathogens in the lungs. Depending upon the signal, AM acquires either classically activated M1 phenotype or alternatively activated M2 phenotype. These phenotypes have specific functions and unique metabolic traits such as upregulated glycolysis and pentose phosphate pathway in M1 phase and enhanced oxidative phosphorylation and tricarboxylic acid cycle during M2 phase that help maintain the sterility of the lungs. In this study, we investigate the metabolic shift in the activated phases of AM (M1 and M2 phase) and highlight the roles of pathways other than the typical players of central carbon metabolism. Pathogenesis is a complex and elongated process where the heightened requirement for energy is matched by metabolic shifts that supplement immune response and maintain homeostasis. The first step of pathogenesis is fever; however, analyzing the role of physical parameters such as temperature is challenging. Here, we observe the effect of an increase in temperature on pathways such as glycolysis, pentose phosphate pathway, oxidative phosphorylation, tricarboxylic acid cycle, amino acid metabolism, and leukotriene metabolism. We report the role of temperature as a catalyst to the immune response of the cell. The activity of pathways such as pyruvate metabolism, arachidonic acid metabolism, chondroitin/heparan sulfate biosynthesis, and heparan sulfate degradation are found to be important driving forces in the M1/M2 phenotype. We have also identified a list of 34 reactions such as nitric oxide production from arginine and the conversion of glycogenin to UDP which play major roles in the metabolic models and prompt the shift of the M2 phenotype to M1 and vice versa. In future, these reactions could further be probed as major contributors in designing effective therapeutic targets against severe respiratory diseases. Author SummaryAlveolar macrophage (AM) is highly plastic in nature and has a wide range of functions including invasion/killing of bacteria to maintaining the homeostasis in the lungs. The regulatory mechanism involved in the alveolar macrophage polarization is essential to fight against severe respiratory conditions (pathogens and particulates). Over the years, experiments on mouse/rat models have been used to draw insightful inferences. However, recent advances have highlighted the lack of transmission from non-human models to successful in vivo human experiments. Hence using genome-scale metabolic (GSM) models to understand the unique metabolic traits of human alveolar macrophages and comprehend the complex metabolic underpinnings that govern the polarization can lead to novel therapeutic strategies. The GSM models of AMs thus far, has not incorporated the activated phases of AM. Here, we aim to exhaustively dissect the metabolic landscape and capabilities of AM in its healthy and activated stages. We carefully explore the changes in reaction fluxes under each of the conditions to understand the role and function of all the pathways with special attention to pathways away from central carbon metabolism. Understanding the characteristics of each phase of AM has applications that could help improve the therapeutic approaches against respiratory conditions.

systems biology↗

bioRxiv2023

Reinforcement learning-guided control strategies for CAR T-cell activation and expansion: Simulation study with a virtual cell culture environment

Reinforcement learning (RL), a subset of machine learning (ML), can potentially optimize and control biomanufacturing processes, such as improved production of therapeutic cells. Here, the process of CAR-T cell activation by antigen presenting beads and their subsequent expansion is formulated in-silico. The simulation is used as an environment to train RL-agents to dynamically control the number of beads in culture with the objective of maximizing the population of robust effector cells at the end of the culture. We make periodic decisions of incremental bead addition or complete removal. The simulation is designed to operate in OpenAI Gym which enables testing of different environments, cell types, agent algorithms and state-inputs to the RL-agent. Agent training is demonstrated with three different algorithms (PPO, A2C and DQN) each sampling three different state input types (tabular, image, mixed); PPO-tabular performs best for this simulation environment. Using this approach, training of the RL-agent on different cell types is demonstrated, resulting in unique control strategies for each type. Sensitivity to input noise (sensor performance), number of control step interventions, and advantage of pre-trained agents are also evaluated. Therefore, we present a general computational framework to maximize the population of robust effector cells in CAR-T cell therapy production. Author SummaryCustom control strategies for expansion and activation of patient-specific CAR T-cell therapies resolved by reinforcement learning using a simulation environment and updatable cell growth parameters.

bioengineering↗

bioRxiv2023

Improved Protocol for Reproducible Human Cortical Organoids Reveals Early Alterations in Metabolism with MAPT Mutations

Human pluripotent stem cell (hPSC)-derived cortical organoids are powerful models but are often limited by low efficiency, variability, and stress-related artifacts. To address these challenges, we developed a scalable organoid platform with end-to-end quality control (QC) metrics spanning manufacturing and single-cell RNA-sequencing (scRNA-seq), developed using eight MAPT mutation isogenic line sets relevant to frontotemporal dementia (FTD-tau). Using a 96 slit-well format, we achieved [~]100% production efficiency across 64 lines. Controlled-release FGF2 enhanced iPSC pluripotency and reduced mesendodermal contaminants, while optimized SB431542 dosing enhanced cortical patterning across lines with variable TGFBR1/ALK5 expression. The resulting organoids displayed transcriptomic profiles and low-stress signatures closely aligned with the developing human cortex. Applying a cortical organoid scRNA-seq index (CortiCOSI), we identified early dysregulation of phosphatase regulators (PPP2CA, ANP32A) and the prefoldin subunit PFDN6 in MAPT V337M excitatory neurons before tau hyperphosphorylation and oligomerization. This platform improves scalability, reproducibility, and mechanistic insight in cortical organoid studies.

neuroscience↗

bioRxiv2023

Multi-organ Metabolic Model of Zea mays Connects Temperature Stress with Thermodynamics-Reducing Power-Energy Generation Axis

Global climate change has severely impacted maize productivity. A holistic understanding of metabolic crosstalk among its organs is essential to address this issue. Thus, we reconstructed the first multi-organ maize genome-scale metabolic model, iZMA6517, and contextualized it with heat and cold stress-related transcriptomics data using the novel EXpression disTributed REAction flux Measurement (EXTREAM) algorithm. Furthermore, implementing metabolic bottleneck analysis on contextualized models revealed fundamental differences between these stresses. While both stresses had reducing power bottlenecks, heat stress had additional energy generation bottlenecks. To tie these signatures, we performed thermodynamic driving force analysis, revealing thermodynamics-reducing power-energy generation axis dictating the nature of temperature stress responses. Thus, for global food security, a temperature-tolerant maize ideotype can be engineered by leveraging the proposed thermodynamics-reducing power-energy generation axis. We experimentally inoculated maize root with a beneficial mycorrhizal fungus, Rhizophagus irregularis, and as a proof of concept demonstrated its potential to alleviate temperature stress. In summary, this study will guide the engineering effort of temperature stress-tolerant maize ideotypes.

plant biology↗

bioRxiv2023

Preserved striatal innervation and motor function despite severe loss of nigral dopamine neurons following mitochondrial dysfunction induced by mtDNA mutations

Degeneration of dopamine neurons in the substantia nigra and their striatal axon terminals causes cardinal motor symptoms of Parkinsons disease (PD). In idiopathic cases, high levels of mitochondrial DNA (mtDNA) mutations associated with mitochondrial dysfunction are a central feature of these vulnerable neurons. Here we present a mouse model expressing the K320E-variant of the mitochondrial helicase Twinkle in dopamine neurons, leading to accelerated mtDNA ageing. K320E-TwinkleDaN mice showed normal motor function at 20 months of age, although already [~]70% of nigral dopamine neurons had perished. The remaining neuron population still preserved [~]75% of axon terminals in the dorsal striatum, which enabled normal dopamine release. Transcriptome analysis and viral tracing confirmed compensatory axonal sprouting of surviving nigral dopamine neurons. We conclude that a small population of substantia nigra neurons can adapt to mtDNA mutations and maintain motor control in mice, holding chances for new treatment strategies in PD patients.

neuroscience↗

bioRxiv2023

Molecular imaging with aquaporin-based reporter genes: quantitative considerations from Monte Carlo diffusion simulations

Aquaporins provide a new class of genetic tools for imaging molecular activity in deep tissues by increasing the rate of cellular water diffusion, which generates magnetic resonance contrast. However, distinguishing aquaporin contrast from the tissue background is challenging because water diffusion is also influenced by structural factors such as cell size and packing density. Here, we developed and experimentally validated a Monte Carlo model to analyze how cell radius and intracellular volume fraction quantitatively affect aquaporin signals. We demonstrated that a differential imaging approach based on time-dependent changes in diffusivity can improve specificity by unambiguously isolating aquaporin-driven contrast from the tissue background. Finally, we used Monte Carlo simulations to analyze the connection between diffusivity and the percentage of cells engineered to express aquaporin, and established a simple mapping that accurately determined the volume fraction of aquaporin-expressing cells in mixed populations. This study creates a framework for broad applications of aquaporins, particularly in biomedicine and in vivo synthetic biology, where quantitative methods to measure the location and performance of genetic devices in whole vertebrates are necessary.

bioengineering↗

bioRxiv2023

Primed to resolve: A single cell atlas of the shoulder capsule reveals a cellular basis for resolving inflammatory fibrosis

Fibrotic conditions are a significant global disease burden. While some therapies delay disease progression, none reverse fibrosis. To gain insights into how fibrosis might resolve, we developed a comparative single cell atlas of frozen shoulder capsule tissue; a chronic inflammatory fibrotic human disease that resolves spontaneously. We identified both a population of pro-inflammatory MERTKlowCD48+ macrophages (M{varphi}) and a population of MERTK+LYVE1+MRC1+M{varphi} enriched for negative regulators of inflammation. Micro-cultures of patient-derived cells identified cell-matrix interactions between MERTK+M{varphi} and DKK3+ and POSTN+ fibroblasts, suggesting that matrix remodelling plays a role in the resolution of frozen shoulder. Cross-tissue analysis revealed a shared gene expression cassette between MERTK+M{varphi} in the shoulder capsule and a similar cell population enriched in synovial tissues from rheumatoid arthritis patients in disease remi ssion, supporting the concept that MERTK+M{varphi} provide a cellular basis for the resolution of inflammation and fibrosis. Single-cell transcriptomic profiling and spatial analysis of human foetal shoulder tissues identified MERTK+LYVE1+MRC1+M{varphi} and DKK3+ and POSTN+ fibroblast populations analogous to those identified in adult shoulder capsule, suggesting that the template to resolve fibrosis is established during development. Therapeutic enhancement of crosstalk between MerTK+M{varphi} and pro-resolving DKK3+ and POSTN+ fibroblasts could accelerate resolution of frozen shoulder and resolve persistent inflammatory fibrotic disease in other tissues.

cell biology↗

bioRxiv2022

Modeling the Sequence Dependence of Differential Antibody Binding in the Immune Response to Infectious Disease

Past studies have shown that incubation of human serum samples on high density peptide arrays followed by measurement of total antibody bound to each peptide sequence allows detection and discrimination of humoral immune responses to a wide variety of infectious disease agents. This is true even though these arrays consist of peptides with near-random amino acid sequences that were not designed to mimic biological antigens. Previously, this immune profiling approach or "immunosignature" has been implemented using a purely statistical evaluation of pattern binding, with no regard for information contained in the amino acid sequences themselves. Here, a neural network is trained on immunoglobulin G binding to 122,926 amino acid sequences selected quasi-randomly to represent a sparse sample of the entire combinatorial binding space in a peptide array using human serum samples from uninfected controls and 5 different infectious disease cohorts infected by either dengue virus, West Nile virus, hepatitis C virus, hepatitis B virus or Trypanosoma cruzi. This results in a sequence-binding relationship for each sample that contains the differential disease information. Processing array data using the neural network effectively aggregates the sequence-binding information, removing sequence-independent noise and improving the accuracy of array-based classification of disease compared to the raw binding data. Because the neural network model is trained on all samples simultaneously, the information common to all samples resides in the hidden layers of the model and the differential information between samples resides in the output layer of the model, one column of a few hundred values per sample. These column vectors themselves can be used to represent each sample for classification or unsupervised clustering applications such as human disease surveillance. Author SummaryPrevious work from Stephen Johnstons lab has shown that it is possible to use high density arrays of near-random peptide sequences as a general, disease agnostic approach to diagnosis by analyzing the pattern of antibody binding in serum to the array. The current approach replaces the purely statistical pattern recognition approach with a machine learning-based approach that substantially enhances the diagnostic power of these peptide array-based antibody profiles by incorporating the sequence information from each peptide with the measured antibody binding, in this case with regard to infectious diseases. This makes the array analysis much more robust to noise and provides a means of condensing the disease differentiating information from the array into a compact form that can be readily used for disease classification or population health monitoring.

immunology↗

bioRxiv2022

Regulation of anterior neurectoderm specification and differentiation by BMP signaling in ascidians

Three palps make the most anterior structure of the ascidian larva. These ectodermal derivatives have both a sensory and adhesive functions essential for metamorphosis. They derive from the anterior neural border and their formation is regulated by signaling pathways such as FGF and Wnt. Since they also share gene expression profiles with vertebrate anterior neural tissue and cranial placodes, their study should shed light on the emergence of the unique vertebrate telencephalon. Here, we show that BMP signaling regulates two phases of palps formation in Ciona intestinalis. During gastrula stages, the anterior neural border marked by Foxc is specified in a domain of inactive BMP signaling, and activating BMP prevented its formation. Later on, inhibiting BMP led to the formation of a single large palp, most likely of dorsal identity. Our results indicate that BMP signaling regulates papilla vs inter-papilla fate decision within the palps forming region. Finally, we showed that modulating BMP signaling led to similar palps phenotypes in another ascidian species Phallusia mammillata. This led us to screen transcriptomic data and identify novel palps markers. Collectively, we provide a better molecular description of palps formation in ascidians that will be instrumental for comparative studies within ascidians and between ascidians and other chordates.

developmental biology↗

bioRxiv2022

Expansion microscopy at one nanometer resolution

Fluorescence imaging is one of the most versatile and widely-used tools in biology1. Although techniques to overcome the diffraction barrier were introduced more than two decades ago, and the nominal attainable resolution kept improving2, 3, fluorescence microscopy still fails to image the morphology of single proteins or small molecular complexes, either purified or in a cellular context4, 5. Here we report a solution to this problem, in the form of one-step nanoscale expansion (ONE) microscopy. We combined the 10-fold axial expansion of the specimen (1000-fold by volume) with a fluorescence fluctuation analysis6, 7 to enable the description of cultured cells, tissues, viral particles, molecular complexes and single proteins. At the cellular level, using immunostaining, our technology revealed detailed nanoscale arrangements of synaptic proteins, including a quasi-regular organisation of PSD95 clusters. At the single molecule level, upon main chain fluorescent labelling, we could visualise the shape of individual membrane and soluble proteins. Moreover, conformational changes undergone by the [~]17 kDa protein calmodulin upon Ca2+ binding were readily observable. We also imaged and classified molecular aggregates in cerebrospinal fluid samples from Parkinsons Disease (PD) patients, which represents a promising new development towards improved PD diagnosis. ONE microscopy is compatible with conventional microscopes and can be performed with the software we provide here as a free, open-source package. This technology bridges the gap between high-resolution structural biology techniques and light microscopy, and provides a new avenue for discoveries in biology and medicine.

biophysics↗

bioRxiv2022

A CNN model for predicting binding affinity changes between SARS-CoV-2 spike RBD variants and ACE2 homologues

The cellular entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) involves the association of its receptor binding domain (RBD) with human angiotensin converting enzyme 2 (hACE2) as the first crucial step. Efficient and reliable prediction of RBD-hACE2 binding affinity changes upon amino acid substitutions can be valuable for public health surveillance and monitoring potential spillover and adaptation into non-human species. Here, we introduce a convolutional neural network (CNN) model trained on protein sequence and structural features to predict experimental RBD-hACE2 binding affinities of 8,440 variants upon single and multiple amino acid substitutions in the RBD or ACE2. The model achieves a classification accuracy of 83.28% and a Pearson correlation coefficient of 0.85 between predicted and experimentally calculated binding affinities in five-fold cross-validation tests and predicts improved binding affinity for most circulating variants. We pro-actively used the CNN model to exhaustively screen for novel RBD variants with combinations of up to four single amino acid substitutions and suggested candidates with the highest improvements in RBD-ACE2 binding affinity for human and animal ACE2 receptors. We found that the binding affinity of RBD variants against animal ACE2s follows similar trends as those against human ACE2. White-tailed deer ACE2 binds to RBD almost as tightly as human ACE2 while cattle, pig, and chicken ACE2s bind weakly. The model allows testing whether adaptation of the virus for increased binding with other animals would cause concomitant increases in binding with hACE2 or decreased fitness due to adaptation to other hosts.

biophysics↗

bioRxiv2021

Autophagy-related protein Atg11 preserves asymmetric inheritance of spindle microtubule-organizing centers

Emerging studies hint at the roles of autophagy-related proteins in various cellular processes in a eukaryotic cell. To understand if autophagy-related proteins influence genome stability, we examined a cohort of 35 autophagy mutants in Saccharomyces cerevisiae. We observed cells lacking Atg11 show poor mitotic stability of minichromosomes. Atg11 molecules dynamically localize to the spindle pole bodies (SPBs). Loss of Atg11 leads to a delayed cell cycle progression. Such cells accumulate at metaphase at an elevated temperature that is relieved when the spindle assembly checkpoint is inactivated. Indeed, atg11{Delta} cells have stabilized securin levels, that prevent anaphase onset, confirming chromosome biorientation defects associated with the mutant. Atg11 functions in the Kar9-dependent spindle positioning pathway and maintains Kar9 asymmetry by facilitating proper dynamic instability of astral microtubules (aMTs). Taken together, this study uncovers a non-canonical role of Atg11 in facilitating MT dynamics crucial for chromosome segregation.

genetics↗

bioRxiv2021

Inactivation mechanism and efficacy of grape seed extract for Human Norovirus surrogate

Proper disinfection of harvested food and water is critical to minimize infectious disease. Grape seed extract (GSE), a commonly used health supplement, is a mixture of plant-derived polyphenols. Polyphenols possess anti-microbial and -fungal properties, but anti-viral effects are not well-known. Here we show that GSE outperformed chemical disinfectants (e.g., free chlorine and peracetic acids) in inactivating Tulane virus, a human norovirus surrogate. GSE induced virus aggregation, an event that correlated with a decrease in virus titers. This aggregation and disinfection was not reversible. Molecular docking simulations indicate that polyphenols potentially formed hydrogen bonds and strong hydrophobic interactions with specific residues in viral capsid proteins. Together, these data suggest that polyphenols physically associate with viral capsid proteins to aggregate viruses as a means to inhibit virus entry into the host cell. Plant-based polyphenols like GSE are an attractive alternative to chemical disinfectants to remove infectious viruses from water or food. ImportanceHuman noroviruses are major food- and water-borne pathogens, causing approximately 20% of all cases of acute gastroenteritis cases in developing and developed countries. Proper sanitation or disinfection are critical strategies to minimize human norovirus-caused disease until a reliable vaccine is created. Grape seed extract (GSE) is a mixture of plant-derived polyphenols that is used as a health supplement. Polyphenols are known for antimicrobial, antifungal, and antibiofilm activities, but antiviral effects are not well-known. In studies here, plant-derived polyphenols outperformed chemical disinfectants (e.g., free chlorine and peracetic acids) in inactivating Tulane virus, a human norovirus surrogate. Based on data from additional molecular assays and molecular docking simulations, the current model is that the polyphenols in GSE bind to the Tulane virus capsid, an event that triggers virion aggregation. It is thought that this aggregation prevents Tulane virus from entering host cells.

biochemistry↗