bluuebunny/crossref_metadata_2025_split huggingface dataset:
The propofol binding sites of prokaryotic voltage-gated sodium channels
Authors: Yang Elaine , Bu Weiming , Suma Antonio , Carnevale Vincenzo , Grasty Kimberly C. , Loll Patrick , Woll Kellie , Bhanu Natarajan , Garcia Benjamin A. , Eckenhoff Roderic G. , Covarrubias Manuel 
Published: October 2020

AbstractPropofol, one of the most commonly used intravenous general anesthetics, modulates neuronal function by interacting with ion channels. The mechanisms that link propofol binding to the modulation of distinct ion channel states, however, are not understood. To tackle this problem, we investigated prokaryotic ancestors of eukaryotic voltage-gated Na+channels (Navs) using unbiased photoaffinity labeling with a photoacitivatable propofol analog (AziPm), electrophysiological methods and mutagenesis. The results directly demonstrate conserved propofol binding sites involving the S4 voltage sensors and the S4-S5 linkers in NaChBac and NavMs, and also suggest state-dependent changes at these sites. Then, using molecular dynamics simulations to elucidate the structural basis of propofol modulation, we show that the S4 voltage sensors and the S4-S5 linkers shape two distinct propofol binding sites in a conformation-dependent manner. These interactions help explain how propofol binding promotes activation-coupled inactivation to inhibit Nav channel function.
Altered neural oscillations and behavior in a genetic mouse model of NMDA receptor hypofunction
Authors: Aguilar David D. , Radzik Leana K. , Schiffino Felipe L. , Folorunso Oluwarotimi , Zielinski Mark R. , Coyle Joseph T. , Balu Darrick T. , McNally James M. 
Published: October 2020

ABSTRACTIntroductionAbnormalities in electroencephalographic (EEG) biomarkers occur in patients with schizophrenia and those clinically at high risk for transition to psychosis and are associated with cognitive impairment. While the pathophysiology of schizophrenia remains poorly understood, converging evidence suggestsN-methyl-D-aspartate receptor (NMDAR) hypofunction plays a central role and likely contributes to biomarker impairments. Thus, the characterization of such biomarkers is of significant interest for both the early diagnosis of schizophrenia and the development of novel treatments.MethodsWe utilized an established model of chronic NMDAR hypofunction, serine racemase knockout (SRKO) mice.In vivoEEG recording and behavioral analyses were performed on adult male and female SRKO mice and wild-type littermates to determine the impact of chronic NMDAR hypofunction on a battery of translationally-relevant electrophysiological biomarkers.ResultsSRKO mice displayed impairments in investigation-elicited gamma power that corresponded with reduced short-term social recognition. This impairment was associated with enhanced background (pre-investigation) broadband gamma activity that only appeared during social task performance. Additionally, SRKO mice exhibited sensory gating impairments, in both gamma power and event-related potential amplitude. However, other biomarkers such as the auditory steady-state response, sleep spindles, and state-specific power spectral density were generally neurotypical.ConclusionsSRKO mice provide a useful model to understand how chronic NMDAR hypofunction contributes to deficits in a subset of translationally-relevant EEG biomarkers that are altered in schizophrenia. Importantly, our gamma band findings support the hypothesis that an aberrant signal-to-noise ratio impairing cognition occurs with NMDAR hypofunction, which may be tied to impaired taskdependent alteration in functional connectivity.
Modulation of polyamine metabolism inArabidopsis thalianaby salicylic acid
Authors: Rossi Franco R. , Gárriz Andrés , Marina María , Pieckenstain Fernando L. 
Published: October 2020

AbstractPolyamines (PAs) play important roles in plant defense against pathogens, but the regulation of PA metabolism by hormone-mediated defense signaling pathways has not been studied in depth. In this study, the modulation of PA metabolism in Arabidopsis by salicylic acid (SA) was analyzed, by combining the exogenous application of this hormone with the use of PA biosynthesis and SA synthesis/signaling mutants. SA induced notable modifications of polyamine metabolism, mainly consisting in putrescine accumulation both in whole-plant extracts and apoplastic fluids. Put was accumulated at the expense of increased biosynthesis by arginine decarboxylase 2 and decreased oxidation by copper amine oxidase. Enhancement of Put levels by SA was independent of the regulatory protein Non-Expressor of Pathogenesis Related 1 (NPR1) and the signaling kinases MKK4 and MPK3, but depended on MPK6. On its part, plant infection byPseudomonas syringaepv.tomatoDC3000 elicited Put accumulation in a SA-dependent way. The present study demonstrates a clear connection between SA signaling and plant PA metabolism in Arabidopsis and contributes to understand the mechanisms by which SA modulates PA levels during plant-pathogen interactions.HighlightSalicylic acid modulates polyamine biosynthesis and catabolism in Arabidopsis. Regulatory effects of salicylic acid are independent of the master regulator NPR1 and are mediated by the MPK6 kinase.
Evaluation of Methods for Protein Representation Learning: A Quantitative Analysis
Authors: Unsal Serbulent , Ataş Heval , Albayrak Muammer , Turhan Kemal , Acar Aybar C. , Doğan Tunca 
Published: October 2020

AbstractData-centric approaches have been utilized to develop predictive methods for elucidating uncharacterized aspects of proteins such as their functions, biophysical properties, subcellular locations and interactions. However, studies indicate that the performance of these methods should be further improved to effectively solve complex problems in biomedicine and biotechnology. A data representation method can be defined as an algorithm that calculates numerical feature vectors for samples in a dataset, to be later used in quantitative modelling tasks. Data representation learning methods do this by training and using a model that employs statistical and machine/deep learning algorithms. These novel methods mostly take inspiration from the data-driven language models that have yielded ground-breaking improvements in the field of natural language processing. Lately, these learned data representations have been applied to the field of protein informatics and have displayed highly promising results in terms of extracting complex traits of proteins regarding sequence-structure-function relations. In this study, we conducted a detailed investigation over protein representation learning methods, by first categorizing and explaining each approach, and then conducting benchmark analyses on;(i)inferring semantic similarities between proteins,(ii)predicting ontology-based protein functions, and(iii)classifying drug target protein families. We examine the advantages and disadvantages of each representation approach over the benchmark results. Finally, we discuss current challenges and suggest future directions. We believe the conclusions of this study will help researchers in applying machine/deep learning-based representation techniques on protein data for various types of predictive tasks. Furthermore, we hope it will demonstrate the potential of machine learning-based data representations for protein science and inspire the development of novel methods/tools to be utilized in the fields of biomedicine and biotechnology.
HiC-ACT: Improved Detection of Chromatin Interactions from Hi-C Data via Aggregated Cauchy Test
Authors: Lagler Taylor M. , Yang Yuchen , Abnousi Armen , Hu Ming , Li Yun 
Published: October 2020

AbstractGenome-wide chromatin conformation capture technologies such as Hi-C are commonly employed to study chromatin spatial organization. In particular, to identify statistically significant long-range chromatin interactions from Hi-C data, most existing methods such as Fit-Hi-C/FitHiC2 and HiCCUPS assume that all chromatin interactions are statistically independent. Such an independence assumption is reasonable at low resolution (e.g., 40Kb bin), but is invalid at high resolution (e.g., 5 or 10Kb bins) since spatial dependency of neighboring chromatin interactions is non-negligible at high resolution. Our previous hidden Markov random field based methods accommodate spatial dependency but are computationally intensive. It is urgent to develop approaches that can model spatial dependence, in a computationally efficient and scalable manner. Here, we develop HiC-ACT, an aggregated Cauchy test (ACT) based approach, to improve the detection of chromatin interactions by post-processing results from methods assuming independence. To benchmark the performance of HiC-ACT, we re-analyzed deeply sequenced Hi-C data from a human lymphoblastoid cell line GM12878 and mouse embryonic stem cell line (mESC). Our results demonstrate advantages of HiC-ACT in improving sensitivity with controlled type-I error. By leveraging information from neighboring chromatin interactions, HiC-ACT enhances the power to detect interactions with lower signal to noise ratio and similar (if not stronger) epigenetic signatures that suggest regulatory roles. We further demonstrate that HiC-ACT peaks show higher overlap with known enhancers than Fit-Hi-C/FitHiC2 peaks, in both GM12878 and mESC. HiC-ACT, effectively a summary statistic based approach, is computationally efficient (~6 minutes and ~2GB memory to process 25,000 pairwise interactions).
Synaptic propagation in neuronal networks with finite-support space dependent coupling
Authors: Erazo Toscano Ricardo , Osan Remus 
Published: October 2020

1AbstractTraveling waves of electrical activity are ubiquitous in biological neuronal networks. Traveling waves in the brain are associated with sensory processing, phase coding, and sleep. The neuron and network parameters that determine traveling waves’ evolution are synaptic space constant, synaptic conductance, membrane time constant, and synaptic decay time constant. We used an abstract neuron model to investigate the propagation characteristics of traveling wave activity. We formulated a set of evolution equations based on the network connectivity parameters. We numerically investigated the stability of the traveling wave propagation with a series of perturbations with biological relevance.
Using EngineeredEscherichia colito Synthesize Squalene with Optimized Manipulation of Squalene Synthase and Mevalonate Pathway
Authors: Sun Chenhao , Ding Yuancheng , Cheng Bingjing , Zong Yeqing 
Published: October 2020

AbstractSqualene is the metabolic precursor of sterols and naturally synthesized in the deep-dea shark liver and human sebum. The utilization of squalene is wide such as food, cosmetical, and pharmaceutical industries. This experiment used engineered Escherichia coli to construct the gene circuit for the biosynthesis of squalene. Human squalene synthase (hSQS) efficiently catalyzes the synthesis of squalene. Also, mevalonate (MVA) pathway would increase the yield of the precursor of squalene, farnesyl diphosphate, which then increased the yield of squalene. Meanwhile, the regulation of MVA pathway via different inducer IPTG concentrations and creation of selection pressure by antibiotics were investigated.
Genomic surveillance and improved molecular typing ofBordetella pertussisusing wgMLST
Authors: Weigand Michael R. , Peng Yanhui , Pouseele Hannes , Kania Dane , Bowden Katherine E. , Williams Margaret M. , Tondella M. Lucia 
Published: October 2020

ABSTRACTMulti-Locus Sequence Typing (MLST) provides allele-based characterization of bacterial pathogens in a standardized framework. However, current MLST schemes forBordetella pertussis, the causative agent of whooping cough, seldom reveal diversity among the small number of gene targets and thereby fail to delineate population structure. To improve discriminatory power of allele-based molecular typing ofB. pertussis, we have developed a whole-genome MLST (wgMLST) scheme from 214 reference-quality genome assemblies. Iterative refinement and allele curation resulted in a scheme of 3,506 coding sequences and covering 81.4% of theB. pertussisgenome. This wgMLST scheme was further evaluated with data from a convenience sample of 2,389B. pertussisisolates sequenced on Illumina instruments, including isolates from known outbreaks and epidemics previously characterized by existing molecular assays, as well as replicates collected from individual patients. wgMLST demonstrated concordance with whole-genome single nucleotide polymorphisms (SNP) profiles, accurately resolved outbreak and sporadic cases in a retrospective comparison, and clustered replicate isolates collected from individual patients during diagnostic confirmation. Additionally, a re-analysis of isolates from two statewide epidemics using wgMLST reconstructed the population structures of circulating strains with increased resolution, revealing new clusters of related cases. Comparison with an existing core-genome (cgMLST) scheme highlights the genomic stability of this bacterium and forms the initial foundation for necessary standardization. These results demonstrate the utility of wgMLST for improvingB. pertussischaracterization and genomic surveillance during the current pertussis disease resurgence.
Infant functional connectivity fingerprints predict long-term language and pre-literacy outcomes
Authors: Yu Xi , Ferradal Silvina , Sliva Danielle D. , Dunstan Jade , Carruthers Clarisa , Sanfilippo Joseph , Zuk Jennifer , Zöllei Lilla , Boyd Emma , Gagoski Borjan , Grant P. Ellen , Gaab Nadine 
Published: October 2020

AbstractFunctional brain networks undergo extensive development within the first few years of life. Previous studies have linked infant functional connectivity to cognitive abilities in toddlerhood. However, little is known regarding the long-term relevance of functional connections established in infancy for the protracted development of higher-order abilities of language and literacy. Employing a five-year longitudinal imaging project starting in infancy, this study utilizes resting-state functional MRI to demonstrate prospective associations between infant functional connectivity fingerprints and subsequent language and foundational literacy skills at a mean age of 6.5. These longitudinal associations are preserved when key environmental influences are controlled for and are independent of emergent language abilities in infancy, suggesting early development of functional network characteristics in supporting the acquisition of high-order language and pre-literacy skills. Altogether, the current results highlight the importance of functional organization established in infancy as a neural scaffold underlying the learning process of complex cognitive functions.
Use-Dependent Plasticity Enhances Nociceptive and Non-Nociceptive Somatosensory Cortical Responses in Healthy Individuals
Authors: Zamorano A.M. , Kleber B. , Arguissain F. , Vuust P. , Flor H. , Graven-Nielsen T. 
Published: October 2020

ABSTRACTRepetitive movements and multisensory integration promote use-dependent plasticity, which has been consistently demonstrated using musical training as a model. Prolonged and repeated execution of motor patterns is also a main risk factor for developing pain syndromes, yet the neural underpinnings that link repetitive movements and use-dependent plasticity to abnormal pain processing in humans are unknown. Employing nociceptive and non-nociceptive electrical stimulation to evoke brain responses, we demonstrate that healthy musicians compared to non-musicians show larger non-nociceptive N140 and nociceptive N200 responses, smaller non-nociceptive P200 responses, and faster reaction times (RTs) to both stimuli. Across participants, larger N140 and N200 amplitudes predicted the RTs, whereas amount of daily practice in musicians predicted RTs, non-nociceptive P200, and nociceptive P300 components. These novel findings indicate that the mechanisms by which repetitive sensorimotor training and multimodal integration promote neural plasticity in multisensory neural structures may also increase stimulus-selectivity to nociceptive cues in healthy individuals.
Ser/Thr kinase-dependent phosphorylation of the peptidoglycan hydrolase CwlA controls its export and modulates cell division inClostridioides difficile
Authors: Garcia-Garcia Transito , Poncet Sandrine , Cuenot Elodie , Douché Thibaut , Gianetto Quentin Giai , Peltier Johann , Courtin Pascal , Chapot-Chartier Marie-Pierre , Matondo Mariette , Dupuy Bruno , Candela Thomas , Martin-Verstraete Isabelle 
Published: October 2020

AbstractCell growth and division require a balance between synthesis and hydrolysis of the peptidoglycan (PG). Inhibition of PG synthesis or uncontrolled PG hydrolysis can be lethal for the cells, making it imperative to control peptidoglycan hydrolase (PGH) activity. The serine/threonine kinases (STKs) of the Hanks family control cell division and envelope homeostasis, but only a few kinase substrates and associated molecular mechanisms have been identified. In this work, we identified CwlA as the first STK-PrkC substrate in the human pathogenClostridiodes difficileand showed that CwlA is an endopeptidase involved in daughter cell separation. We demonstrated that PrkC-dependent phosphorylation inhibits CwlA export, therefore controlling the hydrolytic activity in the cell wall. High level of CwlA at the cell surface led to cell elongation, whereas low level caused cell separation defects. We thus provided evidence that the STK signaling pathway regulates PGH homeostasis to precisely control PG hydrolysis during cell division.
Morphological and biochemical responses ofSphagnummosses to environmental changes
Authors: Sytiuk Anna , Céréghino Regis , Hamard Samuel , Delarue Frédéric , Dorrepaal Ellen , Küttim Martin , Lamentowicz Mariusz , Pourrut Bertrand , Robroek Bjorn JM , Tuittila Eeva-Stiina , Jassey Vincent E.J. 
Published: October 2020

Abstract•Background and AimsSphagnummosses are vital for peatland carbon (C) sequestration, although vulnerable to environmental changes. For averting environmental stresses such as hydrological changes,Sphagnummosses developed an array of morphological and anatomical peculiarities maximizing their water holding capacity. They also produce plethora of biochemicals that could prevent stresses-induced cell-damages but these chemicals remain poorly studied. We aimed to study how various anatomical, metabolites, and antioxidant enzymes vary according toSphagnumtaxonomy, phylogeny and environmental conditions.•MethodsWe conducted our study in fiveSphagnum-dominated peatlands distributed along a latitudinal gradient in Europe, representing a range of local environmental and climate conditions. We examined the direct and indirect effects of latitudinal changes in climate and vegetation species turnover onSphagnumanatomical (cellular and morphological characteristics) and biochemical (spectroscopical identification of primary and specialized metabolites, pigments and enzymatic activities) traits.•Key resultsWe show thatSphagnumtraits were not driven by phylogeny, suggesting that taxonomy and/or environmental conditions prevail on phylogeny in drivingSphagnumtraits variability. We found that moisture conditions were important determinants ofSphagnumanatomical traits, especially those related to water holding capacity. However, the species with the highest water holding capacity also exhibited the highest antioxidant capacity, as showed by the high flavonoid and enzymatic activities in their tissues. Our study further highlighted the importance of vascular plants in drivingSphagnumbiochemical traits. More particularly, we found thatSphagnummosses raises the production of specific compounds such as tannins and polyphenols known to reduce vascular plant capacity when herbaceous cover increases.•ConclusionsOur findings show thatSphagnumanatomical and biochemical traits underpinSphagnumniche differentiation through their role in specialization towards biotic stressors, such as plant competitors, and abiotic stressors, such as hydrological changes, which are important factors governingSphagnumgrowth.
Chitoporin fromSerratia marcescens: recombinant expression, purification and crystallization
Authors: Amornloetwattana Rawiporn , Robinson Robert C. , Soysa Hannadige Sasimali Madusanka , van den Berg Bert , Suginta Wipa 
Published: October 2020

Serratia marcescensis an opportunistic pathogen that commonly causes hospital-acquired infections and can utilize chitin-enriched nutrients as an alternative energy source. This study reports the identification of a chitoporin (ChiP), termedSmChiP, from the outer membrane ofS. marcescens. Sequence alignment with genetically characterized ChiPs suggests thatSmChiP is more closely related to the monomericEcChiP fromEscherichia colithan to the trimericVhChiP fromVibrio campbellii. A single crystal ofSmChiP grown under the condition 22%(w/v) PEG 8000, 0.1 Mcalcium acetate, 0.1 MMES pH 6.0 diffracted X-ray synchrotron radiation to 1.85 Å resolution.SmChiP co-crystallized with chitohexaose under the condition 19%(w/v) PEG 1500, 2 Mammonium phosphate monobasic, 0.1 MHEPES pH 7.0 diffracted X-rays to 2.70 Å resolution. Preliminary crystallographic analysis shows that bothSmChiP crystal forms contain one molecule per asymmetric unit and that they belong to the tetragonal space groupsP42212 andP41212, respectively. TheSmChiP crystal has unit-cell parametersa= 82.97,b= 82.97,c= 189.53 Å, α = β = γ = 90°, while the crystal ofSmChiP in complex with chitohexaose has unit-cell parametersa = 73.24,b= 73.24,c= 213.46 Å, α = β = γ = 90°. Initial assessment of the complex structure clearly revealed electron density for the sugar ligand. Structure determination ofSmChiP in the absence and presence of chitohexaose should reveal the molecular basis of chitin utilization byS. marcescens.