bluuebunny/crossref_metadata_2025_split huggingface dataset:
The JAK2-STAT pathway epigenetically regulates tolerized genes during the first encounter with bacterial antigens
Authors: Lorente-Sorolla Clara , Morante-Palacios Octavio , Garcia-Gomez Antonio , Ciudad Laura , Català-Moll Francesc , Ruiz-Sanmartín Adolfo , Martínez-Gallo Mónica , Ferrer-Roca Ricard , Ruiz-Rodriguez Juan Carlos , Álvarez-Errico Damiana , Ballestar Esteban 
Published: October 2020

ABSTRACTMicrobial challenges, such as widespread bacterial infection, induce endotoxin tolerance. This state of hyporesponsiveness to subsequent infections is mainly displayed by monocytes and macrophages. Endotoxin tolerance is generally acquired following a septic episode. In this study, we investigated DNA methylation changes during the acquisition ofin vitrotolerance. We identified a set of TET2-mediated demethylation events that are specific to toll-like receptor (TLR) 2 and TLR4 stimulation. Lipopolysaccharide (LPS)-specific demethylation occurs at genomic sites that have low accessibility in quiescent monocytes, concomitantly with the transcriptional activation of many inflammation-related genes, and they are enriched in binding motifs for several signal transducer and activator of transcription (STAT) family members. Indeed, STAT1, STAT3 and STAT5, elements of the JAK2 pathway, are phosphorylated in association with the acquisition of endotoxin tolerance. Inhibition of the JAK2 pathway impairs the activation of tolerized genes on the first encounter with LPS. This is evidence of a crucial role for this pathway in determining the initial response of these genes to bacterial antigens and provides a pharmacological target to prevent exacerbated responses, allowing regulated responses upon subsequent challenges. Finally, we assess the pathological relevance of the JAK2 pathway in monocytes from patients with sepsis.
The predator activity landscape predicts the anti-predator behavior and distribution of prey in a tundra community
Authors: Clermont Jeanne , Grenier-Potvin Alexis , Duchesne Éliane , Couchoux Charline , Dulude-de Broin Frédéric , Beardsell Andréanne , Bêty Joël , Berteaux Dominique 
Published: October 2020

AbstractPredation shapes communities through consumptive and non-consumptive effects, where in the latter prey respond to perceived predation risk through risk management strategies occurring at different spatial and temporal scales. The landscape of fear concept is useful to better understand how predation risk affects prey behavioral decisions and distribution, and more generally the spatial dimension of predator-prey relationships. We assessed the effects of the predation risk landscape in a terrestrial Arctic community, where arctic fox is the main predator of ground-nesting bird species. Using high frequency GPS data, we developed a predator activity landscape resulting from fox space use patterns, and validated with an artificial prey experiment that it generated a predation risk landscape. We then investigated the effects of the fox activity landscape on multiple prey, by assessing the anti-predator behavior of a primary prey (snow goose) and the nest distribution of several incidental prey. Areas highly used by foxes were associated with a stronger level of nest defense by snow geese. We further found a lower probability of occurrence of incidental prey nests in areas highly used by foxes, but only for species nesting in habitats easily accessible to foxes. Species nesting in refuges consisting of micro-habitats limiting fox accessibility, like islets, did not respond to the fox activity landscape. Consistent with the scale of the fox activity landscape, this result reflected the capacity of refuges to allow bird nesting without regard to predation risk in the surrounding area. We demonstrated the value of using predator space use patterns to infer spatial variation in predation risk and better understand its effects on prey in landscape of fear studies. We also exposed the diversity of prey risk management strategies, hence refining our understanding of the mechanisms driving species distribution and community structure.
Force transduction creates long-ranged coupling in ribosomes stalled by arrest peptides
Authors: Zimmer Matthew H , Niesen Michiel JM , Miller Thomas F 
Published: October 2020

AbstractForce-sensitive arrest peptides regulate protein biosynthesis by stalling the ribosome as they are translated. Synthesis can be resumed when the nascent arrest peptide experiences a pulling force of sufficient magnitude to break the stall. Efficient stalling is dependent on the specific identity of a large number of amino acids, including amino acids which are tens of angstroms away from the peptidyl transferase center (PTC). The mechanism of force-induced restart and the role of these essential amino acids far from the PTC is currently unknown. We use hundreds of independent molecular dynamics trajectories spanning over 120 μs in combination with kinetic analysis to characterize the barriers along the force-induced restarting pathway for the arrest peptide SecM. We find that the essential amino acids far from the PTC play a major role in controlling the transduction of applied force. In successive states along the stall-breaking pathway, the applied force propagates up the nascent chain until it reaches the C-terminus of SecM and the PTC, inducing conformational changes that allow for restart of translation. A similar mechanism of force propagation through multiple states is observed in the VemP stall-breaking pathway, but secondary structure in VemP allows for heterogeneity in the order of transitions through intermediate states. Results from both arrest peptides explain how residues that are tens of angstroms away from the catalytic center of the ribosome impact stalling efficiency by mediating the response to an applied force and shielding the amino acids responsible for maintaining the stalled state of the PTC.Significance StatementAs nascent proteins are synthesized by the ribosome, their interactions with the environment can create pulling forces on the nascent protein that can be transmitted to the ribosome’s catalytic center. These forces can affect the rate and even the outcome of translation. We use simulations to characterize the pathway of force transduction along arrest peptides and discover how secondary structure in the nascent protein and its interactions with the ribosome exit tunnel impede force propagation. This explains how amino acids in arrest peptides that are tens of angstroms away from the ribosome’s catalytic center contribute to stalling, and, more broadly, suggests how structural features in the nascent protein dictate the ribosome’s ability to functionally respond to its environment.
Evolutionary and phylogenetic insights from a nuclear genome sequence of the extinct, giant ‘subfossil’ koala lemurMegaladapis edwardsi
Authors: Marciniak Stephanie , Mughal Mehreen R. , Godfrey Laurie R. , Bankoff Richard J. , Randrianatoandro Heritiana , Crowley Brooke E. , Bergey Christina M. , Muldoon Kathleen M. , Randrianasy Jeannot , Raharivololona Brigitte M. , Schuster Stephan C. , Malhi Ripan S. , Yoder Anne D. , Louis Edward E. , Kistler Logan , Perry George 
Published: October 2020

AbstractNo endemic Madagascar animal with body mass >10 kg survived a relatively recent wave of extinction on the island. From morphological and isotopic analyses of skeletal ‘subfossil’ remains we can reconstruct some of the biology and behavioral ecology of giant lemurs (primates; up to ~160 kg), elephant birds (up to ~860 kg), and other extraordinary Malagasy megafauna that survived well into the past millennium. Yet much about the evolutionary biology of these now extinct species remains unknown, along with persistent phylogenetic uncertainty in some cases. Thankfully, despite the challenges of DNA preservation in tropical and sub-tropical environments, technical advances have enabled the recovery of ancient DNA from some Malagasy subfossil specimens. Here we present a nuclear genome sequence (~2X coverage) for one of the largest extinct lemurs, the koala lemurMegaladapis edwardsi(~85kg). To support the testing of key phylogenetic and evolutionary hypotheses we also generated new high-coverage complete nuclear genomes for two extant lemur species,Eulemur rufifronsandLepilemur mustelinus, and we aligned these sequences with previously published genomes for three other extant lemur species and 47 non-lemur vertebrates. Our phylogenetic results confirm thatMegaladapisis most closely related to the extant Lemuridae (typified in our analysis byE. rufifrons) to the exclusion ofL. mustelinus, which contradicts morphology-based phylogenies. Our evolutionary analyses identified significant convergent evolution betweenM. edwardsiand extant folivorous primates (colobine monkeys) and ungulate herbivores (horses) in genes encoding protein products that function in the biodegradation of plant toxins and nutrient absorption. These results suggest that koala lemurs were highly adapted to a leaf-based diet, which may also explain their convergent craniodental morphology with the small-bodied folivoreLepilemur.
“Distinct roles of dorsal and ventral subthalamic neurons in action selection and cancellation.”
Authors: Mosher Clayton P. , Mamelak Adam N. , Malekmohammadi Mahsa , Pouratian Nader , Rutishauser Ueli 
Published: October 2020

AbstractThe subthalamic nucleus (STN) supports action selection by inhibiting all motor programs except the desired one. Recent evidence suggests that STN can also cancel an already selected action when goals change, a key aspect of cognitive control. However, there is little neurophysiological evidence for a dissociation between selecting and cancelling actions in the human STN. We recorded single neurons in the STN of humans performing a stop-signal task. Movement-related neurons suppressed their activity during successful stopping whereas stop-signal neurons activated at low-latencies regardless of behavioral outcome. In contrast, STN and motor-cortical beta-bursting occurred only later in the stopping process. Task-related neuronal properties varied by recording location from dorsolateral movement to ventromedial stop-signal tuning. Therefore, action selection and cancellation coexist in STN but are anatomically segregated. These results show that human ventromedial STN neurons carry fast stop-related signals suitable for implementing cognitive control.
The spore of the beans: Spatially explicit models predict coffee rust spread in fragmented landscapes
Authors: Beasley E.M. , Aristizábal N. , Bueno E. , White E.R. 
Published: October 2020

AbstractLandscape structure influences the spread of plant pathogens, primarily by affecting pathogen dispersal. Coffee leaf rust (Hemileia vastatrix), a fungal disease that causes heavy economic losses in the coffee industry, is likely to be affected by landscape structure via dispersal of its wind-borne spores. Previous studies have found positive associations between leaf rust incidence and the proportion of pasture cover, suggesting that deforestation may facilitate rust spore dispersal. We explored this idea by modeling the spread of rust transmission in simulated landscapes. Specifically, we modeled within-patch transmission using a probabilistic cellular automata model, and between-patch transmission using a random walk with spore movement inhibited by forest canopy cover. We used this model to understand how the spread of coffee rust is affected by: 1) clustering of coffee plants, 2) clustering of deforestation, and 3) proportion of landscape deforestation. We found that clustering of coffee plants is the primary driver of rust transmission, affecting the likelihood and severity of rust outbreak. Deforestation is important in landscapes with high clustering of coffee: rust outbreaks are more severe in landscapes with a higher proportion of deforested areas, and more variable in landscapes where deforested areas are more evenly dispersed throughout the landscape.
Replicability of spatial gene expression atlas data from the adult mouse brain
Authors: Lu Shaina , Ortiz Cantin , Fürth Daniel , Fischer Stephan , Meletis Konstantinos , Zador Anthony , Gillis Jesse 
Published: October 2020

AbstractBackgroundSpatial gene expression is particularly interesting in the mammalian brain, with the potential to serve as a link between many data types. However, as with any type of expression data, cross-dataset benchmarking of spatial data is a crucial first step. Here, we assess the replicability, with reference to canonical brain sub-divisions, between the Allen Institute’sin situ hybridizationdata from the adult mouse brain (ABA) and a similar dataset collected using Spatial Transcriptomics (ST). With the advent of tractable spatial techniques, for the first time we are able to benchmark the Allen Institute’s whole-brain, whole-transcriptome spatial expression dataset with a second independent dataset that similarly spans the whole brain and transcriptome.ResultsWe use LASSO, linear regression, and correlation-based feature selection in a supervised learning framework to classify expression samples relative to their assayed location. We show that Allen reference atlas labels are classifiable using transcription, but that performance is higher in the ABA than ST. Further, models trained in one dataset and tested in the opposite dataset do not reproduce classification performance bi-directionally. Finally, while an identifying expression profile can be found for a given brain area, it does not generalize to the opposite dataset.ConclusionsIn general, we found that canonical brain area labels are classifiable in gene expression space within dataset and that our observed performance is not merely reflecting physical distance in the brain. However, we also show that cross-platform classification is not robust. Emerging spatial datasets from the mouse brain will allow further characterization of cross-dataset replicability.
A functional genomic screen inSaccharomyces cerevisiaereveals divergent mechanisms of resistance to different alkylphosphocholine chemotherapeutic agents
Authors: Garcia Jacquelin M. , Schwabe Michael J. , Voelker Dennis R. , Riekhof Wayne R. 
Published: October 2020

AbstractThe alkylphosphocholine (APC) class of antineoplastic and antiprotozoal drugs, such as edelfosine and miltefosine, are structural mimics of lyso-phosphatidylcholine (lyso-PC), and are inhibitory to the yeastSaccharomyces cerevisiaeat low micromolar concentrations. Cytotoxic effects related to inhibition of phospholipid synthesis, induction of an unfolded protein response, inhibition of oxidative phosphorylation, and disruption of lipid rafts have been attributed to members of this drug class, however the molecular mechanisms of action of these drugs remain incompletely understood. Cytostatic and cytotoxic effects of the alkylphosphocholines exhibit variability with regard to chemical structure, leading to differences in effectiveness against different organisms or cell types. We now report the comprehensive identification ofSaccharomyces cerevisiaetitratable-essential gene and haploid non-essential gene deletion mutants that are resistant to the APC drug miltefosine (hexadecyl-O-phosphocholine). 58 strains out of ~5600 tested displayed robust and reproducible resistance to miltefosine. This gene set was heavily enriched in functions associated with vesicular transport steps, especially those involving endocytosis and retrograde transport of endosome derived vesicles to the Golgi or vacuole, suggesting a role for these trafficking pathways in transport of miltefosine to potential sites of action in the endoplasmic reticulum (ER) and mitochondrion. In addition, we identified mutants with defects in phosphatidylinositol-4-phosphate synthesis (TetO::STT4) and hydrolysis (sac1Δ), an oxysterol binding protein homolog (osh2Δ), a number of ER resident proteins, and multiple components of the eisosome. These findings suggest that ER-plasma membrane contact sites and retrograde vesicle transport are involved in the interorganelle transport of lyso-PtdCho and related lyso-phospholipid-like analogs to their intracellular sites of cytotoxic activity.
Understanding the potential benefits of adaptive therapy for metastatic melanoma
Authors: Kim Eunjung , Brown Joel S. , Eroglu Zeynep , Anderson Alexander R.A. 
Published: October 2020

AbstractAdaptive therapy is an evolution-based treatment approach that aims to maintain tumor volume by employing minimum effective drug doses or timed drug holidays. For successful adaptive therapy outcomes, it is critical to find the optimal timing of treatment switch points. Mathematical models are ideal tools to facilitate adaptive therapy dosing and switch time points. We developed two different mathematical models to examine interactions between drug-sensitive and resistant cells in a tumor. The first model assumes genetically fixed drug-sensitive and resistant populations that compete for limited resources. Resistant cell growth is inhibited by sensitive cells. The second model considers phenotypic switching between drug-sensitive and resistant cells. We calibrated each model to fit melanoma patient biomarker changes over time and predicted patient-specific adaptive therapy schedules. Overall, the models predict that adaptive therapy would have delayed time to progression by 6-25 months compared to continuous therapy with dose rates of 6%-74% relative to continuous therapy. We identified predictive factors driving the clinical time gained by adaptive therapy. The first model predicts 6-20 months gained from continuous therapy when the initial population of sensitive cells is large enough, and when the sensitive cells have a large competitive effect on resistant cells. The second model predicts 20-25 months gained from continuous therapy when the switching rate from resistant to sensitive cells is high and the growth rate of sensitive cells is low. This study highlights that there is a range of potential patient specific benefits of adaptive therapy, depending on the underlying mechanism of resistance, and identifies tumor specific parameters that modulate this benefit.
MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamics
Authors: Wu Sean L. , Bennett Jared B. , Sánchez C. Héctor M. , Dolgert Andrew J. , León Tomás M. , Marshall John M. 
Published: October 2020

AbstractInterest in gene drive technology has continued to grow as promising new drive systems have been developed in the lab and discussions are moving towards implementing field trials. The prospect of field trials requires models that incorporate a significant degree of ecological detail, including parameters that change over time in response to environmental data such as temperature and rainfall, leading to seasonal patterns in mosquito population density. Epidemiological outcomes are also of growing importance, as: i) the suitability of a gene drive construct for release will depend on its expected impact on disease transmission, and ii) initial field trials are expected to have a measured entomological outcome and a modeled epidemiological outcome.We present MGDrivE 2 (Mosquito Gene Drive Explorer 2): an extension of and development from the MGDrivE 1 simulation framework that investigates the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. Key strengths and improvements of the MGDrivE 2 framework are: i) the ability of parameters to vary with time and induce seasonal population dynamics, ii) an epidemiological module accommodating reciprocal pathogen transmission between humans and mosquitoes, and iii) an implementation framework based on stochastic Petri nets that enables efficient model formulation and flexible implementation.Example MGDrivE 2 simulations are presented to demonstrate the application of the framework to a CRISPR-based homing gene drive system intended to drive a disease-refractory gene into a population, incorporating time-varying temperature and rainfall data, and predict impact on human disease incidence and prevalence. Further documentation and use examples are provided in vignettes at the project’s CRAN repository.MGDrivE 2 is an open-source R package freely available on CRAN. We intend the package to provide a flexible tool capable of modeling gene drive constructs as they move closer to field application and to infer their expected impact on disease transmission.
Brain preparedness: The proactive role of the cortisol awakening response
Authors: Xiong Bingsen , Chen Changming , Tian Yanqiu , Zhang Shouwen , Liu Chao , Evans Tanya M. , Fernández Guillén , Wu Jianhui , Qin Shaozheng 
Published: October 2020

AbstractUpon awakening from nighttime sleep, the stress hormone cortisol exhibits a burst in the morning within 30-minutes in humans. This cortisol awakening response (CAR) is thought to prepare the brain for upcoming challenges. Yet, the neurobiological mechanisms underlying the CAR-mediated ‘preparation’ function remains unknown. Using blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD-fMRI) with a dedicated prospective design and pharmacological manipulation, we investigated this proactive mechanism in humans across two fMRI studies. In Study 1, we found that a robust CAR was predictive of less hippocampal and prefrontal activity, though enhanced functional coupling between those regions and facilitated working memory performance, during a demanding task later in the afternoon. These results implicate the CAR in proactively promoting brain preparedness based on improved neural efficiency. To address the causality of this proactive effect, we conducted a second study (Study 2) in which we suppressed the CAR with a double blind, placebo controlled, randomized design usingDexamethasone. We found that pharmacological suppression of CAR mirrored the proactive effects from Study 1. Dynamic causal modeling analyses further revealed a reduction of prefrontal top-down modulation over hippocampal activity when performing a cognitively demanding task in the afternoon. These findings establish a causal link between the CAR and its proactive role in optimizing brain functional networks involved in neuroendocrine control and memory.