bluuebunny/crossref_metadata_2025_split huggingface dataset:
REM sleep: unique associations with behavior, corticosterone regulation and apoptotic pathways in chronic stress in mice
Authors: Nollet Mathieu , Hicks Harriet , McCarthy Andrew P. , Wu Huihai , Möller-Levet Carla S. , Laing Emma E. , Malki Karim , Lawless Nathan , Wafford Keith A. , Dijk Derk-Jan , Winsky-Sommerer Raphaelle 
Published: November 2018

AbstractOne of sleep’s putative functions is mediation of adaptation to waking experiences. Chronic stress is a common waking experience, however, which specific aspect of sleep is most responsive, and how sleep changes relate to behavioral disturbances and molecular correlates remain unknown. We quantified sleep, physical, endocrine and behavioral variables and the brain and blood transcriptome in mice exposed to nine weeks of unpredictable chronic mild stress (UCMS). Comparing 46 phenotypical variables revealed that rapid-eye-movement sleep (REMS), corticosterone regulation and coat state were most responsive to UCMS. REMS theta oscillations were enhanced whereas delta oscillations in non-REMS were unaffected. Transcripts affected by UCMS in the prefrontal cortex, hippocampus, hypothalamus and blood were associated with inflammatory and immune responses. A machine learning approach controlling for unspecific UCMS effects identified transcriptomic predictors for specific phenotypes and their overlap. Transcriptomic predictor sets for the inter-individual variation in REMS continuity and theta activity shared many pathways with corticosterone regulation and in particular pathways implicated in apoptosis, including mitochondrial pathways. Predictor sets for REMS and anhedonia, one of the behavioral changes following UCMS, shared pathways involved in oxidative stress, cell proliferation and apoptosis. RNA predictor sets for non-NREMS parameters showed no overlap with other phenotypes. These novel data identify REMS as a core and early element of the response to chronic stress, and identify apoptotic pathways as a putative mechanism by which REMS mediates adaptation to stressful waking experiences.Significance StatementSleep is responsive to experiences during wakefulness and is altered in stress-related disorders. Whether sleep changes primarily concern rapid-eye-movement sleep (REMS) or non-REM sleep, and how they correlate with stress hormones, behavioral and transcriptomic responses remained unknown. We demonstrate using unpredictable chronic (9-weeks) mild stress that REMS is the most responsive of all the measured sleep characteristics, and correlates with deficiency in corticosterone regulation. An unbiased machine learning, controlling for unspecific effects of stress, revealed that REMS correlated with RNA predictor sets enriched in apoptosis including mitochondrial pathways. Several pathways were shared with predictors of corticosterone and behavioral responses. This unbiased approach point to apoptosis as a molecular mechanism by which REMS mediates adaptation to an ecologically relevant waking experience.
Functional network dynamics in a neurodevelopmental disorder of known genetic origin
Authors: Hawkins Erin , Akarca Danyal , Zhang Mengya , Brkic Diandra , Woolrich Mark , Baker Kate , Astle Duncan 
Published: November 2018

AbstractCognitive processing depends on the temporal co-ordination of functional brain networks. This fundamental aspect of neurophysiology potentially bridges the genetic regulation of neuronal activity and developmental cognitive impairments. We investigated brain network dynamics in a neurodevelopmental disorder of known genetic origin, by comparing individuals with ZDHHC9-associated intellectual disability to individuals with no known impairment. We used Hidden Markov Modelling on magnetoencephalography (MEG) data, at rest and during auditory oddball stimulation, to characterise transient network dynamics. At rest, network dynamics distinguished the groups, with ZDHHC9 participants showing longer state activation. Crucially, ZDHHC9 gene expression levels predicted the group differences across networks, supporting an association between molecular pathology and neurophysiology. In contrast, network dynamics during auditory oddball stimulation did not show this association. We demonstrate a link between brain network dynamics and regional gene expression, and present a valuable method for understanding the real-time neural mechanisms linking genetic variation to cognitive difficulties.
Spatio-Genetic and Phenotypic Modelling Elucidates Resistance and Re-Sensitisation to Treatment in Heterogeneous Melanoma
Authors: Hodgkinson Arran , Cam Laurent Le , Trucu Dumitru , Radulescu Ovidiu 
Published: November 2018

AbstractAlthough novel targeted therapies have significantly improved the overall survival of patients with advanced melanoma, understanding and combatting drug resistance remains a major clinical challenge. Using partial differential equations, we describe the evolution of a cellular population through time, space, and phenotype dimensions, in the presence of various drug species. We then use this framework to explore models in which resistance is attained by either mutations (irreversible) or plasticity (reversible). Numerical results suggest that punctuated evolutionary assumptions are more consistent with results obtained from murine melanoma models than gradual evolution. Furthermore, in the context of an evolving tumour cell population, sequencing the treatment, for instance applying immunotherapy before BRAF inhibitors, can increase treatment effectiveness. However, drug strategies which showed success within a spatially homogeneous tumour environment were unsuccessful under heterogeneous conditions, suggesting that spatio-environmental heterogeneity may be the greatest challenge to tumour therapies. Plastic metabolic models are additionally capable of reproducing the characteristic resistant tumour volume curves and predicting re-sensitisation to secondary waves of treatment observed in patient derived xenograft (PDX) melanomas treated with MEK and BRAF inhibitors. Nevertheless, secondary relapse due to a pre-adapted subpopulation, remaining after the first wave of treatment, results in a more rapid development of resistance. Our model provides a framework through which tumour resistance can be understood and would suggest that carefully phased treatments may be able to overcome the development of long-term resistance in melanoma.
Genetic structure in the wood mouse and the bank vole: contrasting patterns in a human-modified and highly fragmented landscape
Authors: Biello Roberto , Brunelli Andrea , Sozio Giulia , Havenstein Katja , Mortelliti Alessio , Ketmaier Valerio , Bertorelle Giorgio 
Published: November 2018

AbstractHabitat fragmentation related to human activities modifies the distribution and the demographic trajectory of a species, often leading to genetic erosion and increased extinction risks. Understanding the impact of fragmentation on different species that co-exist in the same area becomes extremely important. Here we estimated the impact produced by different natural and anthropic landscape features on gene flow patterns in two sympatric species sampled in the same locations. Our main goal was to identify shared and private factors in the comparison among species. 199 bank voles and 194 wood mice were collected in 15 woodlands in a fragmented landscape, and genotyped at 8 and 7 microsatellites, respectively. Genetic variation and structure were analysed with standard approaches. Effective migration surfaces, isolation by resistance analysis, and regression with randomization were used to study isolation by distance and to estimate the relative importance of land cover elements on gene flow. Genetic structure was similarly affected by isolation by distance in these species, but the isolation-by-resistance analysis suggests that i) the wood mouse has constrained patterns of dispersal across woodland patches and facilitated connectivity in cultivated areas; ii) the bank vole connectivity is hindered by urban areas, while permeability is facilitated by the presence of woodlands, and cultivated terrains. Habitat loss and fragmentation can therefore influence genetic structure of small sympatric mammal species in different ways, and predicting the genetic consequences of these events using only one species may be misleading.
Genetic dissection of the different roles of hypothalamic kisspeptin neurons in regulating female reproduction
Authors: Wang Luhong , Vanacker Charlotte , Burger Laura L. , Barnes Tammy , Shah Yatrik M. , Myers Martin G. , Moenter Suzanne M. 
Published: November 2018

AbstractThe brain regulates fertility through gonadotropin-releasing hormone (GnRH) neurons. Estradiol induces negative feedback on pulsatile GnRH/luteinizing hormone (LH) release and positive feedback generating preovulatory GnRH/LH surges. Negative and positive feedback are postulated to be mediated by kisspeptin neurons in arcuate and anteroventral periventricular (AVPV) nuclei, respectively. Kisspeptin-specific ERα knockout mice exhibit disrupted LH pulses and surges. This knockout approach is neither location-specific nor temporally-controlled. We utilized CRISPR-Cas9 to disrupt ERα in adulthood. Mice with ERα disruption in AVPV kisspeptin neurons have typical reproductive cycles but blunted LH surges, associated with decreased excitability of these neurons. Mice with ERα knocked down in arcuate kisspeptin neurons showed disrupted cyclicity, associated with increased glutamatergic transmission to these neurons. These observations suggest activational effects of estradiol regulate surge generation and maintain cyclicity through AVPV and arcuate kisspeptin neurons, respectively, independent from its role in the development of hypothalamic kisspeptin neurons or puberty onset.Significant StatementThe brain regulates fertility through gonadotropin-releasing hormone (GnRH) neurons. Ovarian estradiol regulates GnRH pulses (negative feedback) and the GnRH surge release that ultimately triggers ovulation (positive feedback). Kisspeptin neurons in the arcuate and anteroventral periventricular nuclei are postulated to convey negative and positive feedback to GnRH neurons, respectively. Kisspeptin-specific ERα knockout mice exhibited disrupted negative and positive feedback. However, it is not clear what roles each kisspeptin population plays, and not possible to separate their roles during development vs adulthood in this model. Here we utilized CRISPR-Cas9 to disrupt ERα in each population in adulthood. We found activational effects of estradiol regulate surge generation and maintain cyclicity through AVPV and arcuate kisspeptin neurons, respectively, independent from estradiol action during development.
Transcriptional Feedback Disruption Yields Escape-Resistant Antivirals
Authors: Chaturvedi Sonali , Wolf Marie , Vardi Noam , Du Kelvin , Glazier Joshua , Ke Ruian , Chan Matilda F. , Perelson Alan S. , Weinberger Leor S. 
Published: November 2018

AbstractFrom microbes to cancers, drug-resistant ‘escape’ variants cause significant morbidity and mortality1–7. Here we present proof-of-concept that disruption of viral auto-regulatory (feedback) circuits strongly inhibits viral replication and confers an extremely high barrier to the evolution of resistance. Using DNA duplexes, we develop single-molecule ‘feedback-circuit disruptors’ that interfere with transcriptional negative feedback in human herpesviruses (both Herpes Simplex Virus 1 and Cytomegalovirus) thereby increasing viral transcription factors to cytotoxic levels. Feedback disruptors exhibit low-nanomolar to picomolar IC-50’s, reduce viral replication >100-fold in culture and in mice, and synergize with the standard-of-care antivirals. Strikingly, no feedback-disruptor escape mutants evolved over >60 days of culture, in contrast to approved antivirals to which resistance rapidly evolved. Overall, the results demonstrate that molecular targeting of feedback circuitry could yield escape-resistant antivirals, potentially enabling development of a new class of antimicrobials.
Semi-in vitro Reconstitution of Roseocin, a Two-Component Lantibiotic from an Actinomycete
Authors: Singh Mangal , Sareen Dipti 
Published: November 2018

ABSTRACTLantibiotics are lanthionine containing peptide natural products that belong to the class of ribosomally synthesized and post-translationally modified peptides (RiPPs). Recent expansion in the availability of microbial genomic data and in silico analysis tools have accelerated the discovery of these promising alternatives to antibiotics. Following the genome-mining approach, a biosynthetic gene cluster for a putative two-component lantibiotic roseocin was identified in the genome of an Actinomycete, Streptomyces roseosporus NRRL 11379. Post-translationally modified lanthipeptides of this cluster were obtained by heterologous expression of the genes in E. coli, and were in vitro reconstituted to their bioactive form. The two lanthipeptides displayed antimicrobial activity against Gram-positive bacteria only synergistically, a property reminiscent of two-component lantibiotics. Structural analysis of the α-component identified a disulfide bridge flanking two of its four thioether bridges and the β-component having six thioether bridges with its C-terminus extended than the previously known two-component lantibiotics.
De novo profiling of RNA viruses inAnophelesmalaria vector mosquitoes from forest ecological zones in Senegal and Cambodia
Authors: Belda Eugeni , Minkeu Ferdinand Nanfack , Eiglmeier Karin , Carissimo Guillaume , Holm Inge , Diallo Mawlouth , Diallo Diawo , Vantaux Amélie , Kim Saorin , Sharakhov Igor V. , Vernick Kenneth D. 
Published: November 2018

AbstractBackgroundMosquitoes are colonized by a large but mostly uncharacterized natural virome of RNA viruses.Anophelesmosquitoes are efficient vectors of human malaria, and the composition and distribution of the natural RNA virome may influence the biology and immunity ofAnophelesmalaria vector populations.ResultsAnophelesvectors of human malaria were sampled in forest village sites in Senegal and Cambodia, includingAnopheles funestus, Anopheles gambiaegroup sp., andAnopheles coustaniin Senegal, andAnopheles hyrcanusgroupsp., Anopheles maculatusgroupsp., andAnopheles dirusin Cambodia. Small and long RNA sequences were depleted of mosquito host and de novo assembled to yield non-redundant contigs longer than 500 nucleotides. Analysis of the assemblies by sequence similarity to known virus families yielded 125 novel virus sequences, 39 from SenegalAnophelesand 86 from Cambodia. Important monophyletic virus clades in theBunyaviralesandMononegaviralesorders are found in theseAnophelesfrom Africa and Asia. Small RNA size and abundance profiles were used to cluster non-host RNA assemblies that were unclassified by sequence similarity. 39 unclassified non-redundant contigs >500 nucleotides strongly matched a pattern of classic RNAi processing of viral replication intermediates, and 1566 unclassified contigs strongly matched a pattern consistent with piRNAs. Analysis of piRNA expression inAnopheles coluzziiafter infection with O’nyong nyong virus (familyTogaviridae) suggests that virus infection can specifically alter abundance of some piRNAs.ConclusionsRNA viruses ubiquitously colonize Anopheles vectors of human malaria worldwide. At least some members of the mosquito virome are monophyletic with other arthropod viruses. However, high levels of collinearity and similarity of Anopheles viruses at the peptide level is not necessarily matched by similarity at the nucleotide level, indicating thatAnophelesfrom Africa and Asia are colonized by closely related but clearly diverged virome members. The interplay between small RNA pathways and the virome may represent an important part of the homeostatic mechanism maintaining virome members in a commensal or nonpathogenic state, and host-virome interactions could influence variation in malaria vector competence.
A Framework to Incorporate D-trace Loss into Compositional Data Analysis
Authors: He Shun , Deng Minghua 
Published: November 2018

AbstractThe development of high-throughput sequencing technologies for 16S rRNA gene profiling provides higher quality compositional data for microbe communities. Inferring the direct interaction network under a specific condition and understanding how the network structure changes between two different environmental or genetic conditions are two important topics in biological studies. However, the compositional nature and high dimensionality of the data are challenging in the context of network and differential network recovery. To address this problem in the present paper, we proposed a framework to incorporate the data transformations developed for compositional data analysis into D-trace loss for network and differential network estimation, respectively. The sparse matrix estimators are defined as the minimizer of the corresponding lasso penalized loss. This framework is characterized by its straightforward application based on the ADMM algorithm for numerical solution. Simulations show that the proposed method outperforms other state-of-the-art methods in network and differential network inference under different scenarios. Finally, as an illustration, our method is applied to a mouse skin microbiome data.Author summaryInferring the direct interactions among microbes and how these interactions change under different conditions are important to understand community-wide dynamics. The compositional nature and high dimensionality are two distinctive features of microbial data, which invalidate traditional correlation analysis and challenge interaction network estimation. In this study, we set up a framework that combines data transformation with D-trace loss to infer the direct interaction network and differential network from compositional data. Simulations and real data analysis show that our proposed methods lead to results with higher accuracy and stability.
Protein composition of the occlusion bodies of Epinotia aporema granulovirus
Authors: Masson Tomás , Fabre María Laura , Ferrelli María Leticia , Pidre Matías Luis , Romanowski Víctor 
Published: November 2018

AbstractWithin family Baculoviridae, members of the Betabaculovirus genus are employed as biocontrol agents against lepidopteran pests, either alone or in combination with selected members of the Alphabaculovirus genus. Epinotia aporema granulovirus (EpapGV) is a fast killing betabaculovirus that infects the bean shoot borer (E. aporema) and is a promising biopesticide. Because occlusion bodies (OBs) play a key role in baculovirus horizontal transmission, we investigated the composition of EpapGV OBs. Using mass spectrometry-based proteomics we could identify 56 proteins that are included in the OBs during the final stages of larval infection. Our data provides experimental validation of several annotated hypothetical coding sequences. Proteogenomic mapping against genomic sequence detected a previously unannotated ac110-like core gene and a putative translation fusion product of ORFs epap48 and epap49. Comparative studies of the proteomes available for the family Baculoviridae highlight the conservation of core gene products as parts of the occluded virion. Two proteins specific for betabaculoviruses (Epap48 and Epap95) are incorporated into OBs. Moreover, quantification based on emPAI values showed that Epap95 is one of the most abundant components of EpapGV OBs.
A metapopulation model for the 2018 Ebola virus disease outbreak in Equateur province in the Democratic Republic of the Congo
Authors: Meakin Sophie R. , Tildesley Mike J. , Davis Emma , Keeling Matt J. 
Published: November 2018

AbstractEbola virus disease (EVD) is a viral haemorrhagic fever with high mortality that has caused a number of severe outbreaks in Central and West Africa. Although the majority previous outbreaks have been relatively small, the result of managing outbreaks places huge strains on already limited resources. Mathematical models matched to early case reporting data can be used to identify outbreaks that are at high risk of spreading. Here we consider the EVD outbreak in Equateur Province in the Democratic Republic of the Congo, which was declared on 8 May 2018. We use a simple stochastic metapopulation model to capture the dynamics in the three affected health zones: Bikoro, Iboko and Wangata. We are able to rapidly simulate a large number of realisations and use approximate Bayesian computation, a likelihood-free method, to determine parameters by matching between reported and simulated cases. This method has a number of advantages over more traditional likelihood-based methods as it is less sensitive to errors in the data and is a natural extension to the prediction framework. Using data from 8 to 25 May 2018 we are able to capture the exponential increases in the number of cases in three locations (Bikoro, Iboko and Wangata), although our estimated basic reproductive ratio is higher than for previous outbreaks. Using additional data until 08 July 2018 we are able to detect a decrease in transmission such that the reproductive ratio falls below one. We also estimate the probability of transmission to Kinshasa. We believe this method of fitting models to data offers a generic approach that can deliver rapid results in real time during a range of future outbreaks.
Effect of the Crystal Size of Biogenic Hydroxyapatites on IR and Raman Spectra
Authors: Londoño-Restrepo S.M. , Zubieta-Otero L. F. , Jeronimo-Cruz R. , Mondragon M. A. , Rodriguez-García M. E. 
Published: November 2018

ABSTRACTThis work focuses on the analysis of the impact that raw and calcined biogenic hydroxyapatite crystal size has on the Raman and infrared spectra. To this end, bovine, porcine, and human bones samples were defatted and deproteinized as well as calcinated at 720°C and then analyzed through Raman and Infrared spectroscopies, Transmission Electron Microscopy (TEM), Inductively Coupled Plasma (ICP), and Scanning Electron Microscopy (SEM). Raman and IR spectra for raw samples showed broad bands while after calcination bands became narrow and well defined. TEM images showed that all raw crystallites are nano-plates with a high crystalline quality contrary to the so far well-established concept that biogenic hydroxyapatites have low crystalline quality. This fact confirmed that the broad Raman and infrared bands of raw clean bones come from nanocrystal-plates. SEM analysis confirmed the increase in the size of the crystals after calcination from nano to sub-micron dimensions due to a coalescence phenomenon.
Inference of clonal selection in cancer populations using single-cell sequencing data
Authors: Skums Pavel , Tsivina Vyacheslau , Zelikovsky Alex 
Published: November 2018

AbstractIntra-tumor heterogeneity is one of the major factors influencing cancer progression and treatment outcome. However, evolutionary dynamics of cancer clone populations remain poorly understood. Quantification of clonal selection and inference of fitness landscapes of tumors is a key step to understanding evolutionary mechanisms driving cancer. These problems could be addressed using single cell sequencing, which provides an unprecedented insight into intra-tumor heterogeneity allowing to study and quantify selective advantages of individual clones. Here we present SCIFIL, a computational tool for inference of fitness landscapes of heterogeneous cancer clone populations from single cell sequencing data. SCIFIL allows to estimate maximum likelihood fitnesses of clone variants, measure their selective advantages and order of appearance by fitting an evolutionary model into the tumor phylogeny. We demonstrate the accuracy and utility of our approach on simulated and experimental data. SCIFIL can be used to provide new insight into the evolutionary dynamics of cancer. Its source code is available athttps://github.com/compbel/SCIFIL