bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impaired lysosomal acidification triggers iron deficiency, necrotic cell death and inflammationin vivo
Authors: Yambire King Faisal , Rostosky Christine , Watanabe Takashi , Pacheu-Grau David , Torres-Odio Sylvia , Sanchez-Guerrero Angela , Senderovich Ola , Meyron-Holtz Esther G. , Milosevic Ira , Frahm Jens , West Phillip , Raimundo Nuno 
Published: July 2019

SUMMARYLysosomal acidification is a key feature of healthy cells. Inability to maintain lysosomal acidic pH is associated with aging and neurodegenerative diseases. However, the mechanisms elicited by impaired lysosomal acidification remain unknown. We show here that inhibition of lysosomal acidification triggers cellular iron deficiency, which results in impaired mitochondrial function and necrotic cell death. These effects are recovered by supplying iron via a lysosome-independent pathway. Notably, iron deficiency is sufficient to trigger inflammatory signaling in cultured primary neurons. Using a mouse model of impaired lysosomal acidification, we observed a robust iron deficiency response in the brain, verified byin vivomagnetic resonance imaging. Furthermore, the brains of these mice present a pervasive inflammatory signature associated with instability of mitochondrial DNA (mtDNA), both corrected by supplementation of the mice diet with iron. Our results highlight a novel mechanism linking lysosomal dysfunction, mitochondrial malfunction and inflammationin vivo.
A Membrane-Targeted Photoswitch Potently Modulates Neuronal Firing
Authors: DiFrancesco Mattia L. , Lodola Francesco , Colombo Elisabetta , Maragliano Luca , Paternò Giuseppe M. , Bramini Mattia , Cimò Simone , Colella Letizia , Fazzi Daniele , Eleftheriou Cyril G. , Maya-Vetencourt José Fernando , Bertarelli Chiara , Lanzani Guglielmo , Benfenati Fabio 
Published: July 2019

ABSTRACTOptical technologies allowing modulation of neuronal activity at high spatio-temporal resolution are becoming paramount in neuroscience. We engineered novel light-sensitive molecules by adding polar groups to a hydrophobic backbone containing azobenzene and azepane moieties. We demonstrate that the probes stably partition into the plasma membrane, with affinity for lipid rafts, and cause thinning of the bilayer through their trans-dimerization in the dark. In neurons pulse-labeled with the compound, light induces a transient hyperpolarization followed by a delayed depolarization that triggers action potential firing. The fast hyperpolarization is attributable to a light-dependent decrease in capacitance due to membrane relaxation that follows disruption of the azobenzene dimers. The physiological effects are persistent and can be evoked in vivo after labeling the mouse somatosensory cortex. These data demonstrate the possibility to trigger neural activity in vitro and in vivo by modulating membrane capacitance, without directly affecting ion channels or local temperature.
Intracellular enhancement of BMP signaling by LIM-domain protein FHL3 controls spatiotemporal emergence of the neural crest driven by WNT signaling
Authors: Alkobtawi Mansour , Pla Patrick , Monsoro-Burq Anne H. 
Published: July 2019

AbstractHow multiple morphogen signals are coordinated in space and time to position key embryonic tissues remains elusive. During neural crest formation, bone morphogenetic protein (BMP), fibroblast growth factor (FGF) and WNT signaling cooperate by acting either on the paraxial mesoderm or directly on the neural border ectoderm, but how each tissue interprets this complex information remains poorly understood. Here we show that Fhl3, a scaffold LIM domain protein of previously unknown developmental function, is essential for neural crest formation by linking BMP and WNT signaling thereby positioning the neural crest-inducing signaling center in the paraxial mesoderm. During gastrulation, Fhl3 promotes Smad phosphorylation and Smad-dependentwnt8activation specifically in the paraxial mesoderm, thus modifying the respective mesoderm or ectoderm cell response to the extracellular BMP gradient. This ensures neural border ectoderm specification by the underlying mesoderm via non-cell autonomous WNT signaling. During neurulation, neural crest inducers activatefhl3,promoting BMP/Smad-dependent WNT activity required for neural crest specification. Our findings highlight how Fhl3, acting cell-autonomously, ensures a fine spatial, temporal and germ layer-specific coordination of BMP and WNT signaling at several steps of neural crest development.Highlights:-FHL3 is a novel intracellular enhancer of BMP signaling during early development.-FHL3 ensures cross-talk between BMP and WNT signaling by Smad1-dependent wnt8 activation in the paraxial mesoderm.-FHL3 reiterated function in paraxial mesoderm and in neural border ectoderm is essential for neural crest development at the border of the neural plate.
Tunable genetic devices through simultaneous control of transcription and translation
Authors: Bartoli Vittorio , Meaker Grace A. , Bernardo Mario di , Gorochowski Thomas E. 
Published: July 2019

AbstractSynthetic genetic circuits allow us to modify the behavior of living cells. However, changes in environmental conditions and unforeseen interactions with the host cell can cause deviations from a desired function, resulting in the need for time-consuming reassembly to fix these issues. Here, we use a regulatory motif that controls transcription and translation to create genetic devices whose response functions can be dynamically tuned. This allows us, after construction, to shift the on and off states of a sensor by 4.5- and 28-fold, respectively, and modify genetic NOT and NOR logic gates to allow their transitions between states to be varied over a >6-fold range. In all cases, tuning leads to trade-offs in the fold-change and the ability to distinguish cellular states. This work lays the foundation for adaptive genetic circuits that can be tuned after their physical assembly to maintain functionality across diverse environments and design contexts.
An artificial neural network identifies glyphosate-impacted brackish communities based on 16S rRNA amplicon MiSeq read counts
Authors: Janßen René , Zabel Jakob , von Lukas Uwe , Labrenz Matthias 
Published: July 2019

AbstractArtificial neural networks can be trained on complex data sets to detect, predict, or model specific aspects. Aim of this study was to train an artificial neural network to support environmental monitoring efforts in case of a contamination event by detecting induced changes towards the microbial communities. The neural net was trained on taxonomic cluster count tables obtained via next-generation amplicon sequencing of water column samples originating from a lab microcosm incubation experiment conducted over 140 days to determine the effects of the herbicide glyphosate on succession within brackish-water microbial communities. Glyphosate-treated assemblages were classified correctly; a subsetting approach identified the clusters primarily responsible for this, permitting the reduction of input features. This study demonstrates the potential of artificial neural networks to predict indicator species in cases of glyphosate contamination. The results could empower the development of environmental monitoring strategies with applications limited to neither glyphosate nor amplicon sequence data.Highlight bullet pointsAn artificial neural net was able to identify glyphosate-affected microbial community assemblages based on next generation sequencing dataDecision-relevant taxonomic clusters can be identified by a stochastically subsetting approachJust a fraction of present clusters is needed for classificationFiltering of input data improves classification
Dirichlet-multinomial modelling outperforms alternatives for analysis of microbiome and other ecological count data
Authors: Harrison Joshua G. , Calder W. John , Shastry Vivaswat , Buerkle C. Alex 
Published: July 2019

AbstractMolecular ecology regularly requires the analysis of count data that reflect the relative abundance of features of a composition (e.g., taxa in a community, gene transcripts in a tissue). The sampling process that generates these data can be modeled using the multinomial distribution. Replicate multinomial samples inform the relative abundances of features in an underlying Dirichlet distribution. These distributions together form a hierarchical model for relative abundances among replicates and sampling groups. This type of Dirichlet-multinomial modelling (DMM) has been described previously, but its benefits and limitations are largely untested. With simulated data, we quantified the ability of DMM to detect differences in proportions between treatment and control groups, and compared the efficacy of three computational methods to implement DMM—Hamiltonian Monte Carlo (HMC), variational inference (VI), and Gibbs Markov chain Monte Carlo. We report that DMM was better able to detect shifts in relative abundances than analogous analytical tools, while identifying an acceptably low number of false positives. Among methods for implementing DMM, HMC provided the most accurate estimates of relative abundances, and VI was the most computationally efficient. The sensitivity of DMM was exemplified through analysis of previously published data describing lung microbiomes. We report that DMM identified several potentially pathogenic, bacterial taxa as more abundant in the lungs of children who aspirated foreign material during swallowing; these differences went undetected with different statistical approaches. Our results suggest that DMM has strong potential as a statistical method to guide inference in molecular ecology.
Coronary arterial development is regulated by a Dll4-Jag1-EphrinB2 signaling cascade
Authors: Travisano Stanislao Igor , Oliveira Vera Lucia , Prados Belén , Grego-Bessa Joaquim , Bou Vanesa , Gómez Manuel José , Sánchez-Cabo Fátima , MacGrogan Donal , de la Pompa José Luis 
Published: July 2019

AbstractCoronaries are essential for myocardial growth and heart function. Notch is crucial for mouse embryonic angiogenesis, but its role in coronary development remains uncertain. We show Jag1, Dll4 and activated Notch1 receptor expression in sinus venosus (SV) endocardium. EndocardialJag1removal blocks SV capillary sprouting, whileDll4inactivation stimulates excessive capillary growth, suggesting that ligand antagonism regulates coronary primary plexus formation. Later endothelial ligand removal, or forced expression of Dll4 or the glycosyltransferase MFng, blocks coronary plexus remodeling, arterial differentiation, and perivascular cell maturation. Endocardial deletion ofEfnb2phenocopies the coronary arterial defects of Notch mutants. Angiogenic rescue experiments in ventricular explants, or in primary human endothelial cells, indicate that EphrinB2 is a critical effector of antagonistic Dll4 and Jag1 functions in arterial morphogenesis. Thus, coronary arterial precursors are specified in the SV prior to primary coronary plexus formation and subsequent arterial differentiation depends on a Dll4-Jag1-EphrinB2 signaling cascade.
Detection of novel allelic variations in soybean mutant population using Tilling by Sequencing
Authors: Millas Reneth , Espina Mary , Ahmed CM Sabbir , Bernardini Angelina , Adeleke Ekundayo , Yadegari Zeinab , Dumenyo Korsi , Taheri Ali 
Published: July 2019

ABSTRACTOne of the most important tools in genetic improvement is mutagenesis, which is a useful tool to induce genetic and phenotypic variation for trait improvement and discovery of novel genes. JTN-5203 (MG V) mutant population was generated using an induced ethyl methane sulfonate (EMS) mutagenesis and was used for detection of induced mutations in FAD2-1A and FAD2-1B genes using reverse genetics approach. Optimum concentration of EMS was used to treat 15,000 bulk JTN-5203 seeds producing 1,820 M2 population. DNA was extracted, normalized, and pooled from these individuals. Specific primers were designed from FAD2-1A and FAD2-1B genes that are involved in the fatty acid biosynthesis pathway for further analysis using next-generation sequencing. High throughput mutation discovery through TILLING-by-Sequencing approach was used to detect novel allelic variations in this population. Several mutations and allelic variations with high impacts were detected for FAD2-1A and FAD2-1B. This includes GC to AT transition mutations in FAD2-1A (20%) and FAD2-1B (69%). Mutation density for this population is estimated to be about 1/136kb. Through mutagenesis and high-throughput sequencing technologies, novel alleles underlying the mutations observed in mutants with reduced polyunsaturated fatty acids will be identified, and these mutants can be further used in breeding soybean lines with improved fatty acid profile, thereby developing heart-healthy-soybeans.
Neuromagnetic activation dynamics of stimulus-locked processing during a naturalistic viewing
Authors: Nunes Adonay S. , Kozhemiako Nataliia , Moiseev Alexander , Seymour Robert A. , Cheung Teresa P. L. , Ribary Urs , Doesburg Sam M. 
Published: July 2019

AbstractNaturalistic stimuli such as watching a movie while in the scanner provide an ecologically valid paradigm that has the potential of extracting valuable information on how the brain processes complex stimuli in a short period of time. Naturalistic viewing is also easier to conduct with challenging participant groups including patients and children. Given the high temporal resolution of MEG, in the present study, we demonstrate how a short movie clip can be used to map distinguishable activation dynamics underlying the processing of specific classes of visual stimuli such as face and hand manipulations, as well as auditory stimuli with words and non-words.MEG data were collected from 22 healthy volunteers (6 females, 3 left handed, mean age – 27.7 ± 5.28 years) during the presentation of naturalistic audiovisual stimuli. The MEG data were split into trials with the onset of the stimuli belonging to classes of interest (words, non-words, faces, hand manipulations). Based on the components of the averaged sensor ERFs time-locked to the visual and auditory stimulus onset, four and three time-windows, respectively, were defined to explore brain activation dynamics. Pseudo-Z, defined as the ratio of the source-projected time-locked power to the projected noise power for each vertex, was computed and used as a proxy of time-locked brain activation. Statistical testing using the mean-centered Partial Least Squares analysis indicated periods where a given visual or auditory stimuli had higher activation. Based on peak pseudo-Z differences between the visual conditions, time-frequency resolved analyses were carried to assess beta band desynchronization in motor-related areas, and inter-trial phase synchronization between face processing areas. Our results provide the first evidence that activation dynamics in canonical brain regions associated with the processing of particular classes of visual and auditory stimuli (words, faces, etc.) can be reliably mapped using MEG during presentation of naturalistic stimuli. Given the strength of MEG for brain mapping in temporal and frequency domains, the use of naturalistic stimuli may open new techniques in analyzing brain dynamics during ecologically valid sensation and perception.HighlightsA time-locking analysis was employed in naturalistic stimuli paradigm.Specific visual and auditory stimuli from the movie were mapped in brain space.Motor β-suppression was evident in periods of watching hand manipulation.Increased synchronization between core face-processing areas was found around 200 and 300ms in the face condition.Naturalistic viewing paradigms provide a reliable approach for investigating brain dynamics.
Evidence that the TRPV1 S1-S4 Membrane Domain Contributes to Thermosensing
Authors: Kim Minjoo , Sisco Nicholas J. , Hilton Jacob K. , Montano Camila M. , Castro Manuel A. , Cherry Brian R. , Levitus Marcia , Van Horn Wade D. 
Published: July 2019

AbstractSensing and responding to temperature is crucial in biology. The TRPV1 ion channel is a well-studied heat-sensing receptor that is also activated by vanilloid compounds including capsaicin. Despite significant interest, the molecular underpinnings of thermosensing have remained elusive. The TRPV1 S1-S4 membrane domain couples chemical ligand binding to the pore domain during channel gating. However, the role of the S1-S4 domain in thermosensing is unclear. Evaluation of the isolated human TRPV1 S1-S4 domain by solution NMR, Far-UV CD, and intrinsic fluorescence shows that this domain undergoes a non-denaturing temperature-dependent transition with a high thermosensitivity. Further NMR characterization of the temperature-dependent conformational changes suggests the contribution of the S1-S4 domain to thermosensing shares features with known coupling mechanisms between this domain with ligand and pH activation. Taken together, this study shows that the TRPV1 S1-S4 domain contributes to TRPV1 temperature-dependent activation.
Dicer1 is reduced in APPswe/PSEN1dE9 mice and is regulated by Nrf2
Authors: Wang Yan , Lian Meiling , Zhou Jing , Wu Shengzhou 
Published: July 2019

AbstractThe pathogenesis of Alzheimer’s disease (AD) involves the central roles of oxidative stress. Oxidative stress due to Dicer1 depletion may underline the neurodegeneration in the central nervous system and degeneration of retinal pigment epithelial cells in geographic atrophy form of age-related macular degeneration. We hypothesized that Dicer1 may play roles in AD pathogenesis. Indeed, Dicer1 was reduced in the hippocampus and cortex of APPswe/PSEN1dE9 mice, an AD model. Dicer1 knockdown induced oxidative stress, mitochondrial dysfunction, apoptosis in cultured neurons, and increased secretions of interleukin-1β/-18, indicators of inflammasome activation. Accordingly, Dicer1 was decreased by amyloid peptide and the effect was connected with down-regulation of nuclear factor erythroid 2-related factor 2 (Nrf2). Anti-oxidant response elements (AREs) were identified in the promoter ofDicer1and Keap1-Nrf2-AREs signaling was demonstrated to regulate Dicer1 expression. Furthermore, overexpression of Dicer1 carried by adenovirus in the cultured neurons rescued neurite deficit induced by amyloid peptide. In consistent with thein vitroresults, injection of Dicer1-overexperssion adenovirus in the hippocampus of the AD mice significantly improved spatial learning. Altogether, we unveiled an unexploited roles of Dicer1 in AD and a novel way of Dicer1 regulation. These findings suggest that Dicer1 may be a target in AD therapy.Significance StatementDicer1 is a microRNA-processing enzyme, which is central to microRNA maturation. For the first time, we herein reported that Dicer1 was reduced in the hippocampus or the cortex of AD mice before overt amyloid plque deposition and overexpression of Dicer1 in the hippocampus significantly improved spatial learning in AD mice. We also demonstrated that Dicer1 was regulated by Keap1-Nrf2-ARE signaling which is unreported before. These findings advance understandings of AD pathogenesis and suggest that Dicer1 may be a molecular target in AD therapy.
Implicit visuomotor adaptation remains limited after several days of training
Authors: Wilterson Sarah A. , Taylor Jordan A. 
Published: July 2019

AbstractLearning in sensorimotor adaptation tasks has been viewed as an implicit learning phenomenon. The implicit process affords recalibration of existing motor skills so that the system can adjust to changes in the body or environment without relearning from scratch. However, recent findings suggest that the implicit process is heavily constrained, calling into question its utility in motor learning and the theoretical framework of sensorimotor adaptation paradigms. These inferences have been based mainly on results from single bouts of training, where explicit compensation strategies, such as explicitly re-aiming the intended movement direction, contribute a significant proportion of adaptive learning. It is possible, however, that the implicit process supersedes explicit compensation strategies over repeated practice sessions. We tested this by dissociating the contributions of explicit re-aiming strategies and the implicit process over five consecutive days of training. Despite a substantially longer duration of training, the implicit process still plateaued at a value far short of complete learning and, as has been observed in previous studies, was inappropriate for a mirror reversal task. Notably, we find significant between subject differences that call into question traditional interpretation of these group-level results.Significance StatementIn this set of studies, we find that the implicit process cannot fully account for learning in adaptation tasks, such as the visuomotor rotation and mirror reversal tasks, even following several days of training. In fact, the implicit process can be counterproductive to learning. Most notably, we find significant between subject differences that call into question traditional interpretation of these group-level results.
A Hierarchical Bayesian Mixture Model for Inferring the Expression State of Genes in Transcriptomes
Authors: Thompson Ammon , May Michael R. , Moore Brian R. , Kopp Artyom 
Published: July 2019

Transcriptomes are key to understanding the relationship between genotype and phenotype. The ability to infer the expression state (active or inactive) of genes in the transcriptome offers unique benefits for addressing this issue. For example, qualitative changes in gene expression may underly the origin of novel phenotypes, and expression states are readily comparable between tissues and species. However, inferring the expression state of genes is a surprisingly difficult problem, owing to the complex biological and technical processes that give rise to observed transcriptomic datasets. Here, we develop a hierarchical Bayesian mixture model that describes this complex process, and allows us to infer expression state of genes from replicate transcriptomic libraries. We explore the statistical behavior of this method with analyses of simulated datasets—where we demonstrate its ability to correctly infer true (known) expression states—and empirical-benchmark datasets, where we demonstrate that the expression states inferred from RNA-seq datasets using our method are consistent with those based on independent evidence. The power of our method to correctly infer expression states is generally high and, remarkably, approaches the maximum possible power for this inference problem. We present an empirical analysis of primate-brain transcriptomes, which identifies genes that have a unique expression state in humans. Our method is implemented in the freely-available R package zigzag.Significance StatementHow do the cells of an organism—each with an identical genome—give rise to tissues of incredible phenotypic diversity? Key to answering this question is the transcriptome: the set of genes expressed in a given tissue. We would clearly benefit from the ability to identify qualitative differences in expression (whether a gene is active or inactive in a given tissue/species). Inferring the expression state of genes is surprisingly difficult, owing to the complex biological processes that give rise to transcriptomes, and to the vagaries of techniques used to generate transcriptomic datasets. We develop a hierarchical Bayesian mixture model that—by describing those biological and technical processes—allows us to infer the expression state of genes from replicate transcriptomic datasets.