bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fatty Acid Synthase inhibitor TVB-3166 prevents S-acylation of the Spike protein of human coronaviruses
Authors: Mekhail Katrina , Lee Minhyoung , Sugiyama Michael , Astori Audrey , St-Germain Jonathan , Latreille Elyse , Khosraviani Negar , Wei Kuiru , Li Zhijie , Rini James , Lee Warren L. , Antonescu Costin , Raught Brian , Fairn Gregory D. 
Published: December 2020

AbstractThe Spike protein of SARS-CoV2 and other coronaviruses mediate host cell entry and are S-acylated on multiple phylogenetically conserved cysteine residues. Multiple protein acyltransferase enzymes of the ZDHHC family have been reported to modify Spike proteins post-translationally. Using resin-assisted capture mass spectrometry, we demonstrate that the Spike protein is S-acylated in SARS-CoV2 infected human and monkey cells. We further show that increased abundance of the human acyltransferase ZDHHC5 results in increased S-acylation of the SARS-CoV2 Spike protein, whereasZDHHC5knockout cells had a 40% reduction in the incorporation of an alkynyl-palmitate using click chemistry detection. We also find that the S-acylation of the Spike protein is not limited to palmitate, as clickable versions of myristate and stearate were also found on the immunocaptured protein. Yet, ZDHHC5 was highly selective for palmitate, suggesting that other ZDHHC enzymes mediated the incorporation of other fatty acyl chains. Thus, since multiple ZDHHC isoforms may modify the Spike protein, we examined the ability of the fatty acid synthase inhibitor TVB-3166 to prevent the S-acylation of the Spike proteins of SARS-CoV-2 and human CoV-229E. Treating cells with TVB-3166 inhibited S-acylation of ectopically expressed SARS-CoV2 Spike and attenuated the ability of SARS-CoV2 and human CoV-229E to spreadin vitro.Additionally, treatment of mice with a comparatively low dose of TVB-3166 promoted survival from an otherwise fatal murine coronavirus infection. Our findings further substantiate the necessity of CoV Spike protein S-acylation and the potential use of fatty acid synthase inhibitors.
Modeling of astrocyte networks: towards realistic topology and dynamics
Authors: Verveyko D. V. , Verisokin A. Yu. , Postnov D. E. , Brazhe A. R. 
Published: December 2020

ABSTRACTNeuronal firing and neuron-to-neuron synaptic wiring are currently widely described as orchestrated by astrocytes — elaborately ramified glial cells tiling the cortical and hippocampal space into non-overlapping domains, each covering hundreds of individual dendrites and hundreds thousands synapses. A key component to astrocytic signaling is the dynamics of cytosolic Ca2+which displays multiscale spatiotemporal patterns from short confined elemental Ca2+events (puffs) to Ca2+waves expanding through many cells. Here we synthesize the current understanding of astrocyte morphology, coupling local synaptic activity to astrocytic Ca2+in perisynaptic astrocytic processes and morphology-defined mechanisms of Ca2+regulation in a distributed model. To this end, we build simplified realistic data-driven spatial network templates and compile model equations as defined by local cell morphology. The input to the model is spatially uncorrelated stochastic synaptic activity. The proposed modeling approach is validated by statistics of simulated Ca2+transients at a single cell level. In multicellular templates we observe regular sequences of cell entrainment in Ca2+waves, as a result of interplay between stochastic input and morphology variability between individual astrocytes. Our approach adds spatial dimension to the existing astrocyte models by employment of realistic morphology while retaining enough flexibility and scalability to be embedded in multiscale heterocellular models of neural tissue. We conclude that the proposed approach provides a useful description of neuron-driven Ca2+-activity in the astrocyte syncytium.
Stem cell derived astrocytes withPOLGmutations and mitochondrial dysfunction including abnormal NAD+ metabolism is toxic for neurons
Authors: Liang Kristina Xiao , Kianian Atefeh , Chen Anbin , Kristiansen Cecilie Katrin , Hong Yu , Furriol Jessica , Høyland Lena Elise , Ziegler Mathias , Kråkenes Torbjørn , Tzoulis Charalampos , Sullivan Gareth John , Bindoff Laurence A. 
Published: December 2020

AbstractThe inability to reliably replicate mitochondrial DNA (mtDNA) by mitochondrial DNA polymerase gamma (POLG) leads to a subset of common mitochondrial diseases associated with neuronal death and depletion of neuronal mtDNA. Defining disease mechanisms remains difficult due to the limited access to human tissue. Astrocytes are highly abundant in the brain, playing a crucial role in the support and modulation of neuronal function. Astrocytes also respond to insults affecting the brain. Following damage to the center neural system, which can be hypoxia, inflammation or neurodegeneration, astrocytes become activated and lose their supportive role and gain toxic functions that induce rapid death of neurons and oligodendrocytes. The role of astrocyte reactivation and the consequences this has for neuronal homeostasis in mitochondrial diseases has not been explored. Here, using patient cells carryingPOLGmutations, we generated iPSCs and then differentiated into astrocytes. We demonstrated that POLG-astrocytes exhibited both mitochondrial dysfunctions, including loss of mitochondrial membrane potential, energy failure, complex I and IV defects, disturbed NAD+/NADH metabolism, and mtDNA depletion. Further, POLG derived astrocytes presented an A1-like reactive phenotype with increased proliferation, invasion, upregulation of pathways involved in response to stimulus, immune system process, cell proliferation and cell killing. Under direct and indirect co-culture with neurons, POLG-astrocytes exhibited a toxic effect leading to the death of neurons. Our findings demonstrate that mitochondrial dysfunction caused byPOLGmutations leads not only to intrinsic defects in energy metabolism affecting both neurons and astrocytes, but also to neurotoxic damage driven by astrocytes. Our studies provide a robust astroglia-neuronal interaction model for future investigation of mitochondrial involvement in neurogenesis and neurodegenerative diseases.Highlights▪ Patient-specific astrocytes harbouring aPOLGmutation showed lower mitochondrial membrane potential and mtDNA depletion.▪ POLG-astrocytes generated elevated L-lactate as the end glycolytic product.▪ Patient-specific astrocytes withPOLGmutations exhibited mitochondrial respiratory chain disruption accompanied with abnormal UCP2/SirT1/SirT3 mediated NAD+metabolism.▪ Suppressed complex I and IV-driven respiration contributed to the pathological mechanisms in POLG-related disease.▪ POLG-astrocytes exhibit A1-reactive phenotype and neurotoxic potential.Graphic abstract
Metal microdrive and head cap system for silicon probe recovery in freely moving rodent
Authors: Vöröslakos Mihály , Petersen Peter C. , Vöröslakos Balázs , Buzsáki György 
Published: December 2020

SummaryHigh-yield electrophysiological extracellular recording in freely moving rodents provides a unique window into the temporal dynamics of neural circuits. Recording from unrestrained animals is critical to investigate brain activity during natural behaviors. The use and implantation of high-channel-count silicon probes represent the largest cost and experimental complexity associated with such recordings making a recoverable and reusable system desirable. To address this, we have designed and tested a novel 3D printed head-gear system for freely moving mice and rats. The system consists of a recoverable microdrive printed in stainless steel and a plastic head cap system, allowing researchers to reuse the silicon probes with ease, decreasing the effective cost, and the experimental effort and complexity. The cap designs are modular and provide structural protection and electrical shielding to the implanted hardware and electronics. We provide detailed procedural instructions allowing researchers to adapt and flexibly modify the head-gear system.
From infection to immunity: understanding the response to SARS-CoV2 through in-silico modeling
Authors: Castiglione Filippo , Deb Debashrito , Srivastava Anurag P. , Liò Pietro , Liso Arcangelo 
Published: December 2020

AbstractBackgroundImmune system conditions of the patient is a key factor in COVID-19 infection survival. A growing number of studies have focused on immunological determinants to develop better biomarkers for therapies.AimThe dynamics of the insurgence of immunity is at the core of the both SARS-CoV-2 vaccine development and therapies. This paper addresses a fundamental question in the management of the infection: can we describe the insurgence (and the span) of immunity in COVID-19? The in-silico model developed here answers this question at individual (personalized) and population levels.We simulate the immune response to SARS-CoV-2 and analyze the impact of infecting viral load, affinity to the ACE2 receptor and age in the artificially infected population on the course of the disease.MethodsWe use a stochastic agent-based immune simulation platform to construct a virtual cohort of infected individuals with age-dependent varying degree of immune competence. We use a parameter setting to reproduce known inter-patient variability and general epidemiological statistics.ResultsWe reproducein-silicoa number of clinical observations and we identify critical factors in the statistical evolution of the infection. In particular we evidence the importance of the humoral response over the cytotoxic response and find that the antibody titers measured after day 25 from the infection is a prognostic factor for determining the clinical outcome of the infection.Our modeling framework uses COVID-19 infection to demonstrate the actionable effectiveness of simulating the immune response at individual and population levels. The model developed is able to explain and interpret observed patterns of infection and makes verifiable temporal predictions.Within the limitations imposed by the simulated environment, this work proposes in a quantitative way that the great variability observed in the patient outcomes in real life can be the mere result of subtle variability in the infecting viral load and immune competence in the population.In this work we i) show the power of model predictions, ii) identify the clinical end points that could be more suitable for computational modeling of COVID-19 immune response, iii) define the resolution and amount of data required to empower this class of models for translational medicine purposes and, iv) we exemplify how computational modeling of immune response provides an important view to discuss hypothesis and design new experiments, in particular paving the way to further investigations about the duration of vaccine-elicited immunity especially in the view of the blundering effect of immunesenescence.
Extending the proteomic characterization ofCandida albicansexposed to stress and apoptotic inducers through data-independent acquisition mass spectrometry
Authors: Amador-García Ahinara , Zapico Inés , Malmström Johan , Monteoliva Lucía , Gil Concha 
Published: December 2020

ABSTRACTCandida albicansis a commensal fungus that causes systemic infections in immunosuppressed patients. In order to deal with the changing environment during commensalism or infection,C. albicansmust reprogram its proteome. Characterizing the stress-induced changes in the proteome thatC. albicansuses to survive should be very useful in the development of new antifungal drugs. We studied theC. albicansglobal proteome after exposure to hydrogen peroxide (H2O2) and acetic acid (AA), using a DIA-MS strategy. More than 2000C. albicansproteins were quantified using an ion library previously constructed using DDA-MS.C. albicansresponded to treatment with H2O2with an increase in the abundance of many proteins involved in the oxidative stress response, protein folding and proteasome-dependent catabolism, which led to an increased proteasome activity. The data revealed a previously unknown key role for Prn1, a protein similar to pirins, in the oxidative stress response. Treatment with AA resulted in a general decrease in the abundance of proteins involved in amino acid biosynthesis, protein folding, and rRNA processing. Almost all proteasome proteins declined, as did proteasome activity. Apoptosis was observed after treatment with H2O2, but not AA. A targeted proteomic study of 32 proteins related to apoptosis in yeast supported the results found by DIA-MS and allowed the creation of an efficient method to quantify relevant proteins after treatment with stressors (H2O2, AA, and amphotericin B). This approach also uncovered a main role for Oye32, an oxidoreductase, suggesting this protein as a possible apoptotic marker common to many stressors.IMPORTANCEFungal infections are a worldwide health problem especially in immunocompromised patients and patients with chronic disorders. Invasive candidiasis, mainly caused byC. albicans, are among the most common fungal diseases. Despite the existence of treatments to combat candidiasis the spectra of drugs available are limited. For the discovery of new drug targets is essential to know the pathogen response to different stress conditions. Our study provides a global vision of proteomic remodeling inC. albicansafter exposure to different agents such as hydrogen peroxide, acetic acid and amphotericin B that can cause apoptotic cell death. This results revealed the significance of many proteins related to oxidative stress response and proteasome activity among others. Of note, the discovery of Prn1 as a key protein in the defence against oxidative stress as well the increase in the abundance of Oye32 protein when apoptotic process occurred point out them as possible drug targets.
How optimal allocation of limited testing capacity changes epidemic dynamics
Authors: Calabrese Justin M. , Demers Jeffery 
Published: December 2020

AbstractInsufficient testing capacity continues to be a critical bottleneck in the worldwide fight against COVID-19. Optimizing the deployment of limited testing resources has therefore emerged as a keystone problem in pandemic response planning. Here, we use a modified SEIR model to optimize testing strategies under a constraint of limited testing capacity. We define pre-symptomatic, asymptomatic, and symptomatic infected classes, and assume that positively tested individuals are immediately moved into quarantine. We further define two types of testing. Clinical testing focuses only on the symptomatic class. Non-clinical testing detects pre- and asymptomatic individuals from the general population, and an “information” parameter governs the degree to which such testing can be focused on high infection risk individuals. We then solve for the optimal mix of clinical and non-clinical testing as a function of both testing capacity and the information parameter. We find that purely clinical testing is optimal at very low testing capacities, supporting early guidance to ration tests for the sickest patients. Additionally, we find that a mix of clinical and non-clinical testing becomes optimal as testing capacity increases. At high but empirically observed testing capacities, a mix of clinical testing and unfocused (information=0) non-clinical testing becomes optimal. We further highlight the advantages of early implementation of testing programs, and of combining optimized testing with contact reduction interventions such as lockdowns, social distancing, and masking.
A longitudinal study of the impact of human mobility on the incidence of COVID-19 in India
Authors: Praharaj Sarbeswar , Han Hoon 
Published: December 2020

AbstractHuman mobility plays a crucial role in determining how fast and where infectious diseases can spread. This study aims to investigate visit to which category of places among grocery, retail, parks, workplaces, residential, and transit stations is more associated with the incidence of COVID-19 in India. A longitudinal analysis of generalized estimating equation (GEE) with a Poisson log-linear model is employed to analyze the daily mobility rate and reported new cases of COVID-19 between March 14 and September 11, 2020. This study finds that mobility to places of grocery (food and vegetable markets, drug stores etc.) and retail (restaurants, cafes, shopping centres etc.) is significantly associated (at p<0.01) with the incidence of COVID-19. In contrast, visits to parks, transit stations and mobility within residential neighbourhoods are not statistically significant (p>0.05) in changing COVID-19 cases over time. These findings highlight that instead of blanket lockdown restrictions, authorities should adopt a place-based approach focusing on vulnerable hotspot locations to contain the COVID-19 and any future infectious disease.
Chromosome dynamics and spatial organization during the non-binary cell cycle of a predatory bacterium
Authors: Kaljević Jovana , Saaki Terrens N. V. , Govers Sander K. , Remy Ophélie , van Raaphorst Renske , Lamot Thomas , Laloux Géraldine 
Published: December 2020

AbstractIn bacteria, the dynamics of chromosome replication and segregation are tightly coordinated with cell cycle progression, and largely rely on specific spatiotemporal arrangement of the chromosome. Whereas these key processes are mostly investigated in species that divide by binary fission, they remain mysterious in bacteria producing larger number of descendants. Here, we establish the predatory bacteriumBdellovibrio bacteriovorusas a model to investigate the non-binary processing of a circular chromosome. Our data reveal its extreme compaction in a dense polarized nucleoid. We also show that a first binary-like cycle of replication and asymmetric segregation is followed by multiple asynchronous rounds of replication and progressive ParABS-dependent partitioning, uncoupled from cell division. Surprisingly, ParB localization at the centromere is cell-cycle regulated. Altogether, our findings support a model of complex chromosome choreography, leading to the generation of variable numbers of offspring, highlighting the adaptation of conserved mechanisms to achieve non-binary reproduction in bacteria.
Standardizing a Protocol for Studying pH-dependent Transient Conformations using Computer Simulations
Authors: Singh Ruhar , Lynn Andrew M 
Published: December 2020

1.ABSTRACTUnderstanding pH-dependent protein stability is important in biological - transport, storage, and delivery, in vivoconditions such as aggregation potential in neurodegenerative disease, and in studying the folding/unfolding of proteins. Using computer simulations, we can replace complex experimental determination and provide an atomistic-level interpretation of the cause and effect of pH on protein stability. Here, we standardize a method that provides a framework through which we examined pH-dependent transient conformations during unfolding simulations of proteins. Constant pH simulations utilized in the prediction of pKa values of charged groups of the peptide. The calculated pKa values employed to fix the appropriate protonation state of the amino acid to simulate the effect of pH on the system. Trajectories from multiple high-temperature MD simulations of the protein sample the conformational space during unfolding for a given pH state. The ensemble of conformations is analyzed from its free energy landscape to identify transient and stable conformations both at a given pH and between different pH. As a test system RN80, a protein fragment analog of the C-peptide from bovine pancreatic ribonuclease-A used to measure the accuracy of the predictions from simulations. Experimental measures of the helix content determined as a function of pH display a bell-shaped curve, i.e. RN80 alpha-helix formation is maximum at pH5 with a subsequent loss in helicity at higher and lower pH. The main forces stabilizing the alpha-helix are a salt-bridge formed between Glu-2 and Arg-10 and cation-pi-interaction between Tyr-8 and His-12. Our protocol includes constant pH calculations, optimal high-temperature simulations, and Free Energy landscape analysis exhibited the agreement with the experimental observations.
ScoreNet: A Neural network-based post-processing model for identifying epileptic seizure onset and offset in EEGs
Authors: Boonyakitanont Poomipat , Lek-uthai Apiwat , Songsiri Jitkomut 
Published: December 2020

AbstractWe design an algorithm to automatically detect epileptic seizure onsets and offsets from scalp EEGs. The proposed scheme consists of two sequential steps: detecting seizure episodes from long EEG recordings, and determining seizure onsets and offsets of the detected episodes. We introduce a neural network-based model calledScoreNetto carry out the second step by better predicting the seizure probability of pre-detected seizure epochs to determine seizure onsets and offsets. A cost function calledlog-dice losswith a similar meaning to the F1score is proposed to handle the natural data imbalance inherent in EEG signals signifying seizure events. ScoreNet is then verified on the CHB-MIT Scalp EEG database in combination with several classifiers including random forest, CNN, and logistic regression. As a result, ScoreNet improves seizure detection performance over lone epoch-based seizure classification methods; F1scores increase significantly from 16–37% to 53–70%, and false positive rates per hour decrease from 0.53–5.24 to 0.05–0.61. This method provides clinically acceptable latencies of detecting seizure onset and offset of less than 10 seconds. In addition, aneffective latency indexis proposed as a metric for detection latency whose scoring considers undetected events to provide better insight into onset and offset detection than conventional time-based metrics.
In vitro assessment of the capacity of pesticides to act as agonists/antagonists of the thyroid hormone nuclear receptors
Authors: Zekri Yanis , Agnol Laure Dall , Flamant Frédéric , Guyot Romain 
Published: December 2020

SummarySeveral in vitro tests, including transcriptome analysis of neural cells, were performed to assess the capacity of 33 pesticides to act as thyroid hormone disruptors (THD). Although some pesticides elicit a cellular response, which interferes with thyroid hormone signaling, we found no evidence that they can act as receptor agonists or antagonists. We conclude that the nuclear receptors of thyroid hormone are not common targets of THD, and that pesticide neurodevelopmental toxicity is not explained by a general alteration of neural cell response to thyroid hormone.