bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating spatial and network properties of NMDA-dependent neuronal connectivity in mixed cortical cultures
Authors: Rojvirat Catherine P. , Berlin Joshua R. , Nguyen Tuan D. 
Published: March 2022

ABSTRACTA technique combining fluorescence imaging with Ca2+ indicators and single-cell laser scanning photostimulation of caged glutamate (LSPS) allows identification of functional connections between individual neurons in mixed cultures of rat neocortical cells as well as observation of synchronous spontaneous activity among neurons. LSPS performed on large numbers of neurons yielded maps of functional connections between neurons and allowed calculation of neuronal network parameters. LSPS also provided an indirect measure of excitability of neurons targeted for photostimulation. By repeating LSPS sessions with the same neurons, stability of connections and change in the number and strength of connections were also determined. Experiments were conducted in the presence of bicuculline to study the properties of excitatory neurotransmission. The AMPA receptor inhibitor, 6-Cyano-7-nitroquinoxaline-2,3-dione (CNQX), abolished synchronous neuronal activity but had no effect on connections mapped by LSPS. In contrast, the NMDA receptor inhibitor, 2-Amino-5-phosphono-pentanoic acid (APV), dramatically decreased the number of functional connections between neurons while also affecting synchronous spontaneous activity. Functional connections were also decreased by increasing extracellular Mg2+ concentration. These data demonstrated that LSPS mapping interrogates NMDA receptor-dependent connectivity between neurons in the network. A GluN2A-specific inhibitor, NVP-AAM077, decreased the number and strength of connections between neurons as well as neuron excitability. Conversely, the GluN2A-specific positive modulator, GNE-0723, increased these same properties. These data showed that LSPS can be used to directly study perturbations in the properties of NMDA receptor-dependent connectivity in neuronal networks. This approach should be applicable in a wide variety of in vitro and in vivo experimental preparations.
Gene selection by incorporating genetic networks into case-control association studies
Authors: Cao Xuewei , Liang Xiaoyu , Zhang Shuanglin , Sha Qiuying 
Published: March 2022

AbstractLarge-scale genome-wide association studies (GWAS) have been successfully applied to a wide range of genetic variants underlying complex diseases. The network-based penalized regression approach has been developed to overcome the challenges caused by the computational efficiency for analyzing high-dimensional genomic data by incorporating a biological genetic network. In this paper, we propose a gene selection approach by incorporating genetic networks into case-control association studies for DNA sequence data or DNA methylation data. Instead of using traditional dimension reduction techniques such as principal component analyses and supervised principal component analyses, we use a linear combination of genotypes at SNPs or methylation values at CpG sites in each gene to capture gene-level signals. We develop three approaches for the linear combination: optimally weighted sum (OWS), LD-adjusted polygenic risk score (LD-PRS), and beta-based weighted sum (BWS). OWS and LD-PRS are supervised approaches that depend on the effect of each SNP or CpG site on the case-control status, while BWS can be extracted without using the case-control status. After using one of the linear combinations of genotypes or methylation values in each gene to capture gene-level signals, we regularize them to perform gene selection based on the biological network. Simulation studies show that the proposed approaches have higher true positive rates than using traditional dimension reduction techniques. We also apply our approaches to DNA methylation data and UK Biobank DNA sequence data for analyzing rheumatoid arthritis. The results show that the proposed methods can select potentially rheumatoid arthritis related genes that are missed by existing methods.Author SummaryThere is strong evidence showing that when genes are functionally related to each other in a genetic network, statistical methods utilizing prior biological network knowledge can outperform other methods that ignore genetic network structures. Therefore, statistical methods that can incorporate genetic network information into association analysis in human genetic association studies have been widely used since 2008. Here, we take advantage of recently developed methods to capture the gene-level signals in network-based penalized regression of high-dimensional genetic data. We have shown that the selection performance of our proposed methods can outperform three traditional principal component-based dimension reduction techniques in several simulation scenarios in terms of true positive rates. Meanwhile, by applying our methods in both DNA methylation data and DNA sequence data, the genes identified by our proposed methods can be significantly enriched into the rheumatoid arthritis pathway, such as genesHLA-DMA,HLA-DPB1, andHLA-DQA2in the HLA region.
Physiological trait networks enhance understanding of crop growth and water use in contrasting environments
Authors: Gleason Sean M. , Barnard Dave M. , Green Timothy R. , Mackay D. Scott , Wang Diane R. , Ainsworth Elizabeth A. , Altenhofen Jon , Brodribb Timothy J. , Cochard Hervé , Comas Louise H. , Cooper Mark , Creek Danielle , DeJonge Kendall C. , Delzon Sylvain , Fritschi Felix B. , Hammer Graeme , Hunter Cameron , Lombardozzi Danica , Messina Carlos D. , Ocheltree Troy , Stevens Bo Maxwell , Stewart Jared J. , Vadez Vincent , Wenz Joshua , Wright Ian J. , Yemoto Kevin , Zhang Huihui 
Published: March 2022

Plant function arises from a complex network of structural and physiological traits. Explicit representation of these traits, as well as their connections with other biophysical processes, is required to advance our understanding of plant-soil-climate interactions. We used the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to evaluate physiological trait networks in maize. Net primary productivity (NPP) and grain yield were simulated across five contrasting climate scenarios. Simulations achieving high NPP and grain yield in high precipitation environments featured trait networks conferring high water use strategies: deep roots, high stomatal conductance at low water potential (“risky” stomatal regulation), high xylem hydraulic conductivity, and high maximal leaf area index. In contrast, high NPP and grain yield was achieved in dry environments with low late-season precipitation via water conserving trait networks: deep roots, high embolism resistance, and low stomatal conductance at low leaf water potential (“conservative” stomatal regulation). We suggest that our approach, which allows for the simultaneous evaluation of physiological traits and their interactions (i.e., networks), has potential to improve crop growth predictions in different environments. In contrast, evaluating single traits in isolation of other coordinated traits does not appear to be an effective strategy for predicting plant performance.Summary statementOur process-based model uncovered two beneficial but contrasting trait networks for maize which can be understood by their integrated effect on water use/conservation. Modification of multiple, physiologically aligned, traits were required to bring about meaningful improvements in NPP and yield.
Reproductive barriers and genomic hotspots of adaptation during allopatric species divergence
Authors: Deshmukh Riddhi , Baral Saurav , Kuwalekar Muktai , Kizhakke Athulya Girish , Kunte Krushnamegh 
Published: March 2022

AbstractTheory predicts that in allopatric populations, genomic divergence and reproductive barriers will be driven largely by random genetic drift, and thereby evolve slowly in large populations. However, local adaptation and divergence under selection may also play important roles, which remain poorly characterised. Here we address three key questions in young allopatric species: (a) How widespread are genomic signatures of adaptive divergence?, (b) What is the functional space along which young sister species show divergence at the genomic level?, and (c) How quickly might prezygotic and postzygotic reproductive barriers evolve? Analysis of 82 re-sequenced genomes of the OrientalPapilio polytesspecies group revealed surprisingly widespread hotspots of intense selection and selective sweeps at hundreds of genes unique to each species, and spanning all chromosomes, rather than divergence only in a few genomic islands. These genes perform diverse ecologically important adaptive functions such as wing development, colour patterning, courtship behaviour, mimicry, pheromone synthesis and olfaction, and host plant use and digestion of secondary metabolites, that could contribute to local adaptation and subsequent reproductive isolation. Divergence at such functional genes appeared to have reproductive consequences: behavioural and hybridisation experiments revealed strong assortative mate preference (prezygotic barriers) as well as postzygotic barriers to hybridisation in timespans as short as 1.27 my, indicating that speciation was already complete, rather than incipient. Our study thus demonstrates an underappreciated role of intense selection and potential local adaptation in creating genome-wide hotspots of rapid molecular evolution and divergence, during differentiation and speciation in young allopatric species.
Chemogenetic enhancement of cAMP signaling renders hippocampal synaptic plasticity resilient to the impact of acute sleep deprivation
Authors: Walsh Emily Nicole , Shetty Mahesh Shivarama , Diba Kamran , Abel Ted 
Published: March 2022

AbstractSleep facilitates memory storage and even brief periods of sleep loss lead to impairments in memory, particularly memories that are hippocampus dependent. In previous studies, we have shown that the deficit in memory seen after sleep loss is accompanied by deficits in synaptic plasticity. Our previous work has also found that sleep deprivation is associated with reduced levels of cyclic adenosine monophosphate (cAMP) in the hippocampus, and that the reduction of cAMP mediates the diminished memory performance. Based on these findings, we hypothesized that cAMP acts as a mediator for not only the cognitive deficits caused by sleep deprivation, but also the observed deficits in synaptic plasticity. In this study, we expressed the heterologousDrosophila melanogasterGαs-protein coupled octopamine receptor (DmOctβ1R) in mouse hippocampal neurons. This receptor is selectively activated by the systemically injected ligand (octopamine), thus allowing us to increase cAMP levels in hippocampal neurons during a five-hour sleep deprivation period. Our results show that chemogenetic enhancement of cAMP during the period of sleep deprivation prevents deficits in a persistent form of long-term potentiation (LTP) that is induced at the Schaffer collateral synapses in the hippocampal CA1 region. We also found that elevating cAMP levels only in the early or later half of sleep deprivation successfully prevented LTP deficits. These findings reveal that cAMP-dependent signaling pathways are key mediators of sleep deprivation at the synaptic level. Targeting these pathways could be useful in designing strategies to prevent the impact of sleep loss.Significance statementInsufficient sleep is an issue with significant health and socioeconomic implications. This includes a negative impact on memory consolidation. Previous studies in mice found that acute sleep deprivation leads to deficits in hippocampal synaptic plasticity and memory, which are associated with reduced levels of the signaling molecule cAMP. In this study, we used a chemogenetic strategy to enhance cAMP levels in specific hippocampal neurons during sleep deprivation. We found that this made synaptic plasticity resilient to the negative effects of sleep deprivation. These findings reveal that cAMP-dependent signaling pathways are key mediators of sleep deprivation and that targeting these pathways could be useful in designing strategies to prevent the impact of sleep loss.
A Microengineered Brain-Chip to Model Neuroinflammation in Humans
Authors: Pediaditakis I. , Kodella K. R. , Manatakis D. V. , Le C. Y. , Barthakur S. , Sorets A. , Gravanis A. , Ewart L. , Rubin L. L. , Manolakos E. S. , Hinojosa C. D. , Karalis K. 
Published: March 2022

SUMMARYSpecies differences in the brain and the blood-brain barrier (BBB) biology hamper the translation from animal models to humans and impede the development of specific therapeutics for brain diseases. Here we present a human Brain-Chip engineered to recapitulate critical aspects of the complex brain cell-cell interactions that mediate neuroinflammation development. Our human organotypic microphysiological system (MPS) includes endothelial-like cells, pericytes, glia, and cortical neurons and maintains BBB permeability at in vivo relevant levels, providing a significant improvement in complexity and clinical mimicry compared to previous MPS models. This is the first report of a Brain-Chip with an RNA expression profile close to that of the adult human cortex and that demonstrates advantages over Transwell culture. Through perfusion of TNF-α, we recreated key inflammatory features, such as glia activation, the release of proinflammatory cytokines, and increased barrier permeability. Our model may provide a reliable tool for mechanistic studies in neuron-glial interactions and dysregulation of BBB function during neuroinflammation.
LIPA-driven hydrolysis of cholesteryl arachidonate promotes cancer metastasis via NF-κB
Authors: Chen Zhicong , Chen Fukai , Lee Hyeon Jeong , Zhang Meng , Yin Xianglin , Dai Mingji , Cheng Ji-Xin 
Published: March 2022

AbstractCholesteryl ester (CE) is an established marker in many types of aggressive cancers. Yet, the function of CE homeostasis during cancer progression is largely unknown. Here, enabled by Raman spectromicroscopy, pan-cancer bioinformatic analysis, and biocompatible Raman probe of cholesterol, LIPA was identified as the key regulator of CE hydrolysis in cancer cells. LIPA inhibition induced aberrant accumulation of CE-rich lipid droplet at single cell level. LIPA-driven CE hydrolysis was directly visualized by stimulated Raman scattering imaging of alkyne-tagged cholesterol. Cholesteryl arachidonate was identified as a dominant substrate that is rapidly hydrolyzed by LIPA. Inhibition of LIPA effectively suppressed cancer metastasis both in vitro and in vivo. Mechanistically, LIPA inhibition suppresses NF-κB signaling, while the NF-κB members positively regulate the expression level of LIPA, indicating regulation of CE homeostasis by a LIPA-CE-NFκB feedback loop. Collectively, our findings reveal that LIPA drives CE hydrolysis during cancer progression and is an important metabolic target for cancer therapy.
Asymmetrical lineage introgression and recombination in populations ofAspergillus flavus: implications for biological control
Authors: Molo Megan S. , White James B. , Cornish Vicki , Gell Richard M , Baars Oliver , Singh Rakhi , Carbone Mary Anna , Isakeit Thomas , Wise Kiersten A. , Woloshuk Charles P. , Bluhm Burton H. , Horn Bruce W. , Heiniger Ron W. , Carbone Ignazio 
Published: March 2022

ABSTRACTAspergillus flavusis an agriculturally important fungus that causes ear rot of maize and produces aflatoxins (AFs), of which B1is the most potent carcinogen known. In the US, the management of AFs includes the deployment of biological control agents that comprise two nonaflatoxigenicA. flavusstrains, either Afla-Guard® (member of lineage IB) or AF36 (lineage IC). We used genotyping-by-sequencing to examine the influence of both biocontrol agents on native populations ofA. flavusin cornfields in Texas, North Carolina, Arkansas, and Indiana. This study examined up to 27,529 single-nucleotide polymorphisms (SNPs) in a total of 815A. flavusisolates, and 353 genome-wide haplotypes sampled before biocontrol application, three months after biocontrol application, and up to three years after initial application. Here, we report that the two distinctA. flavusevolutionary lineages IB and IC differ significantly in their frequency distributions across states. We provide evidence of increased unidirectional gene flow from lineage IB into IC, inferred to be due to the applied Afla-Guard biocontrol strain. Genetic exchange and recombination of biocontrol strains with native strains was detected in as little as three months after biocontrol application and up to one and three years later. There was limited inter-lineage migration in the untreated fields. These findings suggest that biocontrol products that include strains from lineage IB offer the greatest potential for sustained reductions in aflatoxin levels over several years. This knowledge has important implications for developing new biocontrol strategies.
High-throughput Production of Diverse Xenobiotic Metabolites with P450-transduced Huh7 Hepatoma Cell Lines
Authors: Lee Choon-Myung , Liu Ken H. , Singer Grant , Miller Gary W. , Li Shuzhao , Jones Dean P. , Morgan Edward T. 
Published: March 2022

AbstractPrecision medicine requires methods to assess drug metabolism and distribution, including the identification of known and undocumented drug and chemical exposures as well as their metabolites. Recent work demonstrated high-throughput generation of xenobiotic metabolites with human liver S-9 fractions and detection in human plasma and urine. Here, we developed a panel of lentivirally transduced human hepatoma cell lines (Huh7) that stably express individual cytochrome P450 (P450) enzymes and generate P450-specific xenobiotic metabolites. We verified protein expression by immunoblotting and demonstrated that the cell lines generate P450-specific metabolites from probe substrates. To increase analytical throughput, we used a pooling strategy where 36 chemicals were grouped into 12 unique mixtures, each mixture containing 6 randomly selected compounds, and each compound being present in two separate mixtures. Each mixture of compounds was incubated with 8 different P450 cell lines with cell extracts analyzed at 0 and 2 h. Extracts were analyzed using liquid chromatography-high resolution mass spectrometry. Cell lines selectively metabolized test substrates, with pazopanib metabolized by CYP3A4 and CYP2C8 cells, bupropion by CYP2B6, and β-naphthoflavone by CYP1A2 for example, showing substrate-enzyme specificity. Predicted metabolites from the remaining 33 compounds as well as many unidentified m/z features were detected. We also show that a specific metabolite generated by CYP2B6 cells, but not detected in the S9 system, was identified in human samples. Our data show that incubating these cell lines with chemical mixtures accelerated characterization of xenobiotic chemical space, while simultaneously allowing for the contributions of specific P450 enzymes to be identified.Significance statementHigh resolution mass spectrometry enables the identification of exposures to drugs and other xenobiotics in human samples. This paper demonstrates a workflow for high throughput production of xenobiotic metabolites using a panel of engineered cytochrome P450-expressing hepatoma cells. Active substrate-enzyme pairs can be identified using this workflow and generated metabolites can be used as surrogate standards to validate xenobiotic detection in humans.
Examination of diurnal variation and sex differences in hippocampal neurophysiology and spatial memory
Authors: Goode Lacy K. , Fusilier Allison R. , Remiszewski Natalie , Reeves Jacob M. , Abiraman Kavitha , Defenderfer Matthew , Paul Jodi R. , McMahon Lori L. , Gamble Karen L. 
Published: March 2022

AbstractCircadian rhythms are biological processes that cycle across 24 hours and regulate many facets of neurophysiology, including learning and memory. Circadian variation in performance on spatial memory tasks is well-documented; however, the effect of sex across circadian time remains unclear. Additionally, little is known regarding the impact of time-of-day on hippocampal neuronal physiology. Here, we investigated the influence of both sex and time-of-day on hippocampal neurophysiology and memory.Performance on the object location memory (OLM) task depended on both circadian time and sex, with memory enhanced at night in males but during the day in females. Long-term synaptic potentiation (LTP) magnitude at CA3-CA1 synapses was greater at night compared to day in both sexes. Next, we measured spontaneous synaptic excitation and inhibition onto CA1 pyramidal neurons. Frequency and amplitude of inhibition was greater during the day compared to night, regardless of sex. Frequency and amplitude of excitation was larger in females, compared to males, independent of time-of-day, although both time-of-day and sex influenced presynaptic release probability. At night, CA1 pyramidal neurons showed enhanced excitability (action potential firing and/or baseline potential) that was dependent on synaptic excitation and inhibition, regardless of sex. This study emphasizes the importance of sex and time-of-day in hippocampal physiology, especially given that many neurological disorders impacting the hippocampus are linked to circadian disruption and present differently in men and women. Knowledge about how sex and circadian rhythms affect hippocampal physiology can improve the translational relevancy of therapeutics and inform the appropriate timing of existing treatments.
The SARS-CoV-2 Delta variant induces an antibody response largely focused on class 1 and 2 antibody epitopes
Authors: Greaney Allison J. , Eguia Rachel T. , Starr Tyler N. , Khan Khadija , Franko Nicholas , Logue Jennifer K. , Lord Sandra M. , Speake Cate , Chu Helen Y. , Sigal Alex , Bloom Jesse D. 
Published: March 2022

AbstractExposure histories to SARS-CoV-2 variants and vaccinations will shape the specificity of antibody responses. To understand the specificity of Delta-elicited antibody immunity, we characterize the polyclonal antibody response elicited by primary or mRNA vaccine-breakthrough Delta infections. Both types of infection elicit a neutralizing antibody response focused heavily on the receptor-binding domain (RBD). We use deep mutational scanning to show that mutations to the RBD’s class 1 and class 2 epitopes, including sites 417, 478, and 484–486 often reduce binding of these Delta-elicited antibodies. The anti-Delta antibody response is more similar to that elicited by early 2020 viruses than the Beta variant, with mutations to the class 1 and 2, but not class 3 epitopes, having the largest effects on polyclonal antibody binding. In addition, mutations to the class 1 epitope (e.g., K417N) tend to have larger effects on antibody binding and neutralization in the Delta spike than in the D614G spike, both for vaccine- and Delta-infection-elicited antibodies. These results help elucidate how the antigenic impacts of SARS-CoV-2 mutations depend on exposure history.