bluuebunny/crossref_metadata_2025_split huggingface dataset:
Loss of one Engrailed1 allele enhances induced α-synucleinopathy
Authors: Chatterjee Diptaman , Sanchez Daniel Saiz , Quansah Emmanuel , Rey Nolwen L , George Sonia , Becker Katelyn , Madaj Zachary , Steiner Jennifer A , Ma Jiyan , Escobar Galvis Martha L , Kordower Jeffrey H , Brundin Patrik 
Published: January 2019

AbstractBackground:Parkinson’s disease (PD) is a synucleinopathy that has multiple neuropathological characteristics, with nigrostriatal dopamine system degeneration being a core feature. Current models of PD pathology typically fail to recapitulate several attributes of the pathogenic process and neuropathology. We aimed to define the effects of combining a mouse model exhibiting multiple PD-like changes with intrastriatal injections of α-synuclein (α-syn) pre-formed fibrils (PFFs) aggregates. We employed the heterozygous Engrailed 1 (En1+/-) mouse that features several pathophysiological hallmarks of clinical PD. Objective: To test the hypothesis that the neuropathological changes in the En1+/- mice will promote formation of α-syn aggregates following intrastriatal injections of pathogenic human α-syn PFFs. Methods: We unilaterally injected PFFs into the striata of 1 month-old En1+/- and control wild-type mice and euthanized animals at 3 months for post-mortem analysis. Results: Using immunohistochemistry and unbiased stereology, we established that PFF-injected En1+/- mice exhibited a near-threefold increase in pS129-α-syn-positive neurons in the substantia nigra compared to PFF-injected wild-type mice. The PFF-injected En1+/- mice also displayed significant increases in pS129-α-syn-positive neurons in the amygdala and ventral tegmental area; regions of known PD pathology with projections to the striatum. Additionally, we observed amplified pS129-α-syn-positive aggregation in En1+/- mice in multiple cortical regions. Conclusions: Following intrastriatal injection of PFFs, absence of an En1 allele leads to additional aggregation of pathological α-syn, potentially due to En1-loss mediated nigrostriatal impairment. We propose that further development of this double-hit model could be predictive of pre-clinical therapeutic potential and success for PD than existing mouse models.
Lupin (Lupinus sp.) seeds exert anthelmintic activity associated with their alkaloid content
Authors: Dubois O. , Allanic C. , Charvet C. L. , Guégnard F. , Février H. , Théry-Koné I. , Cortet J. , Koch C. , Bouvier F. , Fassier T. , Marcon D. , Magnin-Robert J.B. , Peineau N. , Courtot E. , Huau C. , Meynadier A. , Enguehard-Gueiffier C. , Neveu C. , Boudesocque-Delaye L. , Sallé G. 
Published: January 2019

AbstractThe growing expansion range of drug resistant parasitic nematode populations threatens the sustainability of ruminant farming worldwide. In this context, nutraceuticals, i.e. feed that would both fulfil dietary requirements while ensuring parasite control, would contribute to increase farming sustainability in developed and low resource settings. In this study, we characterized the anthelmintic potential of lupin seed extracts against major ruminant trichostrongylids, i.e. H. contortus and T. circumcincta. Our observations showed that total seed extracts from commercially available lupin varieties significantly inhibited larval migration. This anthelmintic effect was sustained on multidrug resistant field isolate and across parasite species and was mediated by the seed alkaloid content. Analytical chemistry revealed a set of four lupanine and sparteine-derivatives with anthelmintic activity and electrophysiology assays on recombinant nematode acetylcholine receptors suggested an antagonistic mode of action for lupin alkaloids. While commercial lupin seeds did not exert direct anthelmintic effect in H. contortus infected lupin-fed ewes and goats, it significantly dampened blood production losses suffered by goats. Lupin seed extracts hence provide a working basis for the development of novel anthelmintic compounds able to break drug resistance in the field, while they could be used to increase the resilience of infected dairy ruminants.
Exploring Environmental Coverages of Species: A New Variable Selection Methodology for Rulesets from the Genetic Algorithm for Ruleset Prediction
Authors: Yang Anni , Gomez Juan Pablo , Blackburn Jason K. 
Published: January 2019

AbstractVariable selection for, and determination of variable importance within, species distribution models (SDMs) remain an important area of research with continuing challenges. Most SDM algorithms provide normally exhaustive searches through variable space, however, selecting variables to include in models is a first challenge. The estimation of the explanatory power of variables and the selection of the most appropriate variable set within models can be a second challenge. Although some SDMs incorporate the variable selection rubric inside the algorithms, there is no integrated rubric to evaluate the variable importance in the Genetic Algorithm for Ruleset Production (GARP). Here, we designed a novel variable selection methodology based on the rulesets generated from a GARP experiment. The importance of the variables in a GARP experiment can be estimated based on the consideration of the prevalence of each environmental variable in the dominant presence rules of the best subset of models and its coverage. We tested the performance of this variable selection method based on simulated species with both weak and strong responses to simulated environmental covariates. The variable selection method generally performed well during the simulations with over 2/3 of the trials correctly identifying most covariates. We then predict the distribution of Bacillus anthracis (the bacterium that causes anthrax) in the continental United States (US) and apply our variable selection procedure as a real-world example. We found that the distribution of B. anthracis was primarily determined by organic content, soil pH, calcic vertisols, vegetation, sand fraction, elevation, and seasonality in temperature and moisture.
Benzoate-TolerantEscherichia coliStrains from Experimental Evolution Lose the Gad Regulon, Multi-Drug Efflux Pumps, and Hydrogenases
Authors: Moore Jeremy P. , Li Haofan , Engmann Morgan L. , Bischof Katarina M. , Kunka Karina S. , Harris Mary E. , Tancredi Anna C. , Ditmars Frederick S. , Basting Preston J. , George Nadja S. , Bhagwat Arvind A. , Slonczewski Joan L. 
Published: January 2019

ABSTRACTBenzoate, a partial uncoupler of the proton motive force (PMF), selects for sensitivity to chloramphenicol and tetracycline inEscherichia coliK-12. Genetic mechanisms of increased benzoate tolerance and decreased drug resistance were analyzed in strains isolated from experimental evolution with benzoate. Transcriptomes showed reversal of benzoate-dependent regulation, including the Gad regulon for acid resistance and multi-drug resistance (MDR). Benzoate-evolved strains knocked down the nitrate reductasenarHJand the acid-consuming hydrogenase Hyd-3, but upregulated OmpF and other porins that admit nutrients and antibiotics. Mutations were found affecting many genes of aromatic catabolism such asfolDandadd. Several candidate genes from benzoate-evolved strains had a role in benzoate tolerance. Growth with benzoate or salicylate was increased by deletion of the Gad activatorariR, or by deletion of theslp-gadXacid fitness island encoding Gad regulators and the MDR pump MdtEF. Benzoate growth was also increased by deletion of MDR componentemrA, the RpoS post-transcriptional regulatorcspC, or the adenosine deaminaseadd. Growth in chloramphenicol with benzoate was decreased by a point mutation in the RNA polymerase alpha-subunitrpoA, which appeared in one chloramphenicol-sensitive benzoate-evolved strain. Growth in chloramphenicol was also decreased by deletion of Mar activatorrob, or ofrfaY(lipopolysaccharide biosynthesis). Hydrogenase Hyd-3 deletion increased benzoate tolerance. Overall, long-term culture in the presence of benzoate or salicylate favors loss of MDR efflux pumps and of hydrogenases that generate a futile cycle of PMF; and favors upregulation of large-hole porins that increase uptake of fermentable nutrients and of antibiotics.IMPORTANCEBenzoate is a common food preservative, and salicylate is the active form of aspirin. InE. coli, benzoate derivatives upregulate multiple regulons that export antibiotics and other toxic products, and downregulate large outer-membrane porins that allow antibiotic influx. But benzoate or salicylate exposure causes energy stress by depleting the proton motive force. In the absence of antibiotics, long-term benzoate exposure selects against energy-spending systems such as multi-drug efflux pumps and the proton-consuming hydrogenase. Selection favors upregulation of porins that admit fermentable substrates but also allow entry of antibiotics. Thus, evolution with benzoate requires a tradeoff for antibiotic sensitivity. Benzoate and salicylate are naturally occurring plant signal molecules that may influence the evolution of microbiomes in plants and in animal digestive tracts. Effects on hydrogenase activity may be relevant to the biotechnology of hydrogen production.
BOLD signatures of sleep
Authors: Song Chen , Boly Melanie , Tagliazucchi Enzo , Laufs Helmut , Tononi Giulio 
Published: January 2019

ABSTRACTSleep can be distinguished from wake by changes in brain electrical activity, typically assessed using electroencephalography (EEG). The hallmark of non-rapid-eye-movement sleep are two major EEG events: slow waves and spindles. Here we sought to identify possible signatures of sleep in brain hemodynamic activity, using simultaneous fMRI-EEG. We found that, during the transition from wake to sleep, blood-oxygen-level-dependent (BOLD) activity evolved from a mixed-frequency pattern to one dominated by two distinct oscillations: a low-frequency (~0.05Hz) oscillation prominent in light sleep and a high-frequency (~0.17Hz) oscillation in deep sleep. The two BOLD oscillations correlated with the occurrences of spindles and slow waves, respectively. They were detectable across the whole brain, cortically and subcortically, but had different regional distributions and opposite onset patterns. These spontaneous BOLD oscillations provide fMRI signatures of basic sleep processes, which may be employed to study human sleep at spatial resolution and brain coverage not achievable using EEG.HIGHLIGHTSspontaneous BOLD oscillations differentiate sleep from wakelow-frequency BOLD oscillation tracks sleep spindleshigh-frequency BOLD oscillation tracks sleep slow wavesBOLD oscillations provide fMRI signatures of key sleep processes
Tumor-Intrinsic Response to IFNγ Shapes the Tumor Microenvironment and Anti-PD-1 Response in NSCLC
Authors: Bullock Bonnie L. , Kimball Abigail K. , Poczobutt Joanna M. , Li Howard Y. , Kwak Jeff W. , Neuwelt Alexander J. , Johnson Amber M. , Kleczko Emily , Kaspar Rachael , Hopp Katharina , Schenk Erin , Weiser-Evans Mary C. M. , Clambey Eric T. , Nemenoff Raphael A. 
Published: January 2019

AbstractTargeting PD-1/ PD-L1 is only effective in ~20% of lung cancer patients, but determinants of this response are poorly defined. We previously observed differential responses of two murine K-Ras lung cancer cell lines to anti-PD-1 therapy: CMT167 tumors were eliminated while LLC tumors were resistant. The goal of this study was to define mechanism(s) mediating this difference. RNA-Seq analysis of cancer cells recovered from lung tumors revealed that CMT167 cells induced an IFNγ signature that was absent in LLC cells. Silencing Ifngr1 in CMT167 resulted in tumors resistant to IFNγ and anti-PD-1 therapy. Conversely, LLC cells had high basal expression of Socs1, an inhibitor of IFNγ. Silencing Socs1 increased response to IFNγ in vitro and sensitized tumors to anti-PD-1. This was associated with a reshaped TME, characterized by enhanced T cell infiltration and enrichment of PD-L1 high myeloid cells. These studies demonstrate that targeted enhancement of tumor-intrinsic IFNγ signaling can induce of cascade of changes associated with increased therapeutic vulnerability.SummaryMechanisms regulating response to anti-PD-1 therapy in lung cancer are not well defined. This study, using orthotopic immunocompetent mouse models of lung cancer, demonstrates that intrinsic sensitivity of cancer cells to IFNγ determines anti-PD-1 responsiveness through alterations in the tumor microenvironment.
Computational Geometric Tools for Modeling Inherent Variability in Animal Behavior
Authors: Stamps Matthew T. , Go Soo , Mathuru Ajay S. 
Published: January 2019

ABSTRACTA fundamental challenge for behavioral neuroscientists is to represent inherent variability among animals accurately without compromising the ability to quantify differences between conditions. We developed two new methods that apply curve and shape alignment techniques to address this issue. As a proof-of-concept we applied these methods to compare normal or alarmed behavior in pairs of medaka (Oryzias latipes). The curve alignment method we call Behavioral Distortion Distance (BDD) revealed that alarmed fish display less predictable swimming over time, even if individuals incorporate the same action patterns like immobility, sudden changes in swimming trajectory, or changing their position in the water column. The Conformal Spatiotemporal Distance (CSD) technique on the other hand revealed that, in spite of the unpredictability, alarmed individuals share an overall swim pattern, possibly accounting for the widely held notion of “stereotypy” in alarm responses. More generally, we propose that these new applications of known computational geometric techniques are useful in combination to represent, compare, and quantify complex behaviors consisting of common action patterns that differ in duration, sequence, or frequency.
Coupling adaptive molecular evolution to phylodynamics using fitness-dependent birth-death models
Authors: Rasmussen David A. , Stadler Tanja 
Published: January 2019

AbstractBeneficial and deleterious mutations cause fitness to vary among individuals in a population, which natural selection can then act upon to drive adaptive evolution. Non-neutral mutations can likewise cause fitness to vary among lineages in a phylogeny and thereby shape its branching structure. While standard phylogenetic models do not allow mutations to feedback and shape tree topology, birth-death models can account for this feedback by letting the fitness of lineages vary depending on their type. To date though, these multi-type birth-death models have only been applied to cases where a lineage’s fitness is determined by a single evolving character state and have not been extended to model sequence evolution across multiple sites. We introduce an extension of the multi-type birth-death model, the marginal fitness birth-death model, that tracks sequence evolution at multiple sites and how the fitness of a lineage depends on its genotype across all sites. This approach remains computationally tractable even for many evolving sites because it tracks the genotype of a lineage probabilistically in an approximate manner, and then marginalizes over all possible genotypes to determine the expected fitness of a lineage. Although approximate, we show that we can accurately estimate the fitness of a lineage and even site-specific mutational fitness effects from the branching pattern of a phylogeny. To demonstrate the power of this approach, we apply it to estimate the host population level fitness effects of mutations previously identified to increase the infectivity of Ebola virus in human cell lines during the 2013-16 epidemic in West Africa.
Prefrontal oscillations modulate the propagation of neuronal activity required for working memory
Authors: Sherfey Jason S. , Ardid Salva , Miller Earl K. , Hasselmo Michael E. , Kopell Nancy J. 
Published: January 2019

AbstractCognition involves using attended information, maintained in working memory (WM), to guide action. During a cognitive task, a correct response requires flexible, selective gating so that only the appropriate information flows from WM to downstream effectors that carry out the response. In this work, we used biophysically-detailed modeling to explore the hypothesis that network oscillations in prefrontal cortex (PFC), leveraging local inhibition, can independently gate responses to items in WM. The key role of local inhibition was to control the period between spike bursts in the outputs, and to produce an oscillatory response no matter whether the WM item was maintained in an asynchronous or oscillatory state. We found that the WM item that induced an oscillatory population response in the PFC output layer with the shortest period between spike bursts was most reliably propagated. The network resonant frequency (i.e., the input frequency that produces the largest response) of the output layer can be flexibly tuned by varying the excitability of deep layer principal cells. Our model suggests that experimentally-observed modulation of PFC beta-frequency (15-30 Hz) and gamma-frequency (30-80 Hz) oscillations could leverage network resonance and local inhibition to govern the flexible routing of signals in service to cognitive processes like gating outputs from working memory and the selection of rule-based actions. Importantly, we show for the first time that nonspecific changes in deep layer excitability can tune the output gate’s resonant frequency, enabling the specific selection of signals encoded by populations in asynchronous or fast oscillatory states. More generally, this represents a dynamic mechanism by which adjusting network excitability can govern the propagation of asynchronous and oscillatory signals throughout neocortex.
Phototrophic Methane Oxidation in a Member of the Chloroflexi Phylum
Authors: Ward Lewis M. , Shih Patrick M. , Hemp James , Kakegawa Takeshi , Fischer Woodward W. , McGlynn Shawn E. 
Published: January 2019

AbstractBiological methane cycling plays an important role in Earth’s climate and the global carbon cycle, with biological methane oxidation (methanotrophy) modulating methane release from numerous environments including soils, sediments, and water columns. Methanotrophy is typically coupled to aerobic respiration or anaerobically via the reduction of sulfate, nitrate, or metal oxides, and while the possibility of coupling methane oxidation to phototrophy (photomethanotrophy) has been proposed, no organism has ever been described that is capable of this metabolism. Here we described a new bacterial genome from a member of the Chloroflexi phylum—termed hereCandidatusChlorolinea photomethanotrophicum—with cooccurring methanotrophy and phototrophy pathways, suggesting a novel link between these two metabolisms. Recovered as a metagenome-assembled genome from microbial mats in an iron-rich hot spring in Japan,Ca.‘C. photomethanotrophicum’ forms a new lineage within the Chloroflexi phylum and expands the known metabolic diversity of this already diverse clade.Ca.‘C. photomethanotrophicum’ appears to be metabolically versatile, capable of phototrophy (via a Type 2 reaction center), aerobic respiration, nitrite reduction, oxidation of methane and carbon monoxide, and potentially carbon fixation via a novel pathway composed of hybridized components of the serine cycle and the 3-hydroxypropionate bicycle. The biochemical network of this organism is constructed from components from multiple organisms and pathways, further demonstrating the modular nature of metabolic machinery and the ecological and evolutionary importance of horizontal gene transfer in the establishment of novel pathways.SignificanceMethane is a major greenhouse gas, and the production and consumption of methane is largely driven by the metabolism of microorganisms. Although it has been hypothesized for decades that some bacteria may be capable of growth by eating methane and conserving energy from sunlight (photomethanotrophy), this metabolism has never been discovered in nature. Here, we describe the first genetic evidence for a bacterium capable of photomethanotrophy, adding a new pathway to the known diversity of how microbes can make a living. This discovery also adds a new link to the global carbon cycle, and may provide new opportunities for designing biotechnological tools for processing methane.
SLM-Transform: A Method for Memory-Efficient Indexing of Spectra for Database Search in LC-MS/MS Proteomics
Authors: Haseeb Muhammad , Awan Muaaz G. , Cadigan Alexander S. , Saeed Fahad 
Published: January 2019

AbstractThe most commonly used strategy for peptide identification in shotgun LC-MS/MS proteomics involves searching of MS/MS data against an in-silico digested protein sequence database. Typically, the digested peptide sequences are indexed into the memory to allow faster search times. However, subjecting a database to post-translational modifications (PTMs) during digestion results in an exponential increase in the number of peptides and therefore memory consumption. This limits the usage of existing fragment-ion based open-search algorithms for databases with several PTMs. In this paper, we propose a novel fragment-ion indexing technique which is analogous to suffix array transformation and allows constant time querying of indexed ions. We extend our transformation method, called SLM-Transform, by constructing ion buckets that allow querying of all indexed ions by mass by only storing information on distribution of ion-frequencies within buckets. The stored information is used with a regression technique to locate the position of ions in constant time. Moreover, the number of theoretical b- and y-ions generated and indexed for each theoretical spectrum are limited. Our results show that SLM-Transform allows indexing of up to 4x peptides than other leading fragment-ion based database search tools within the same memory constraints. We show that SLM-Transform based index allows indexing of over 83 million peptides within 26GB RAM as compared to 80GB required by MSFragger. Finally, we show the constant ion retrieval time for SLM-Transform based index allowing ultrafast peptide search speeds.Source code will be made available at: https://github.com/pcdslab/slmindex