bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microstructures amplify carotenoid plumage signals in colorful tanagers
Authors: McCoy Dakota E. , Shultz Allison J. , Vidoudez Charles , van der Heide Emma , Trauger Sunia A. , Haig David 
Published: October 2019

AbstractRed, orange, and yellow carotenoid-colored plumages have been considered honest signals of condition. We comprehensively quantified carotenoid signals in the social, sexually-dimorphic tanager genusRamphocelususing scanning electron microscopy (SEM), finite-difference time-domain (FDTD) optical modeling, liquid chromatography–mass spectrometry (LC-MS), and spectrophotometry. Despite males having significantly more saturated color patches, males and females within a species have equivalent amounts and types of carotenoids. Male, but not female, feathers have elaborate microstructures which amplify color appearance. Expanded barbs enhance color saturation (for the same amount of pigment) by increasing the transmission of optical power through the feather. Dihedral barbules (vertically-angled, strap-shaped barbules) reduce total reflectance to generate “super black” plumage, an optical illusion to enhance nearby color. Dihedral barbules paired with red carotenoid pigment produce “velvet red” plumage. Together, our results suggest that a widely cited index of honesty—carotenoid pigments—cannot fully explain male appearance. We propose that males are selected to evolve amplifiers of honest signals—in this case, microstructures that enhance appearance —that are not necessarily themselves linked to quality.
A powerful subset-based gene-set analysis method identifies novel associations and improves interpretation in UK Biobank
Authors: Dutta Diptavo , VandeHaar Peter , Fritsche Lars G. , Zöllner Sebastian , Boehnke Michael , Scott Laura J. , Lee Seunggeun 
Published: October 2019

AbstractTests of association between a phenotype and a set of genes in a biological pathway can provide insights into the genetic architecture of complex phenotypes beyond those obtained from single variant or single gene association analysis. However, most existing gene set tests have limited power to detect gene set-phenotype association when a small fraction of the genes are associated with the phenotype, and no method exists which identifies the potentially “active” genes that might drive a gene-set-based association. To address these issues, we have developed Gene-set analysis Association Using Sparse Signals (GAUSS), a method for gene-set association analysis that requires only GWAS summary statistics. For each significantly associated gene set, GAUSS identifies the subset of genes that have the maximal evidence of association and can best account for the gene set association. Using pre-computed correlation structure among test statistics from a reference panel, our p-value calculation is substantially faster than other permutation or simulation-based approaches. In simulations with varying proportions of causal genes, we find that GAUSS effectively controls type 1 error rate and has greater power than several existing methods, particularly when a small proportion of genes account for the gene set signal. Using GAUSS, we analyzed UK Biobank GWAS summary statistics for 10,679 gene-sets and 1,403 binary phenotypes. We found that GAUSS is scalable and identified 13,466 phenotype and gene-set association pairs. Within these genes sets, we identify an average of 17.2 (max=405) genes that underlie these gene set associations.
Fast and precise single-cell data analysis using hierarchical autoencoder
Authors: Tran Duc , Nguyen Hung , Tran Bang , La Vecchia Carlo , Luu Hung N. , Nguyen Tin 
Published: October 2019

AbstractA primary challenge in single-cell RNA sequencing (scRNA-seq) studies comes from the massive amount of data and the excess noise level. To address this challenge, we introduce a hierarchical autoencoder that reliably extracts representative information of each cell. In an extensive analysis, we demonstrate that the approach vastly outperforms state-of-the-art techniques in many research sub-fields of scRNA-seq analysis, including cell segregation through unsupervised learning, visualization of transcriptome landscape, cell classification, and pseudo-time inference.
Genetic relatedness cannot explain social preferences in black-and-white ruffed lemurs (Varecia variegata)
Authors: Baden Andrea L , Webster Timothy H , Bradley Brenda J 
Published: October 2019

ABSTRACTFission-fusion social dynamics are common among a number of vertebrate taxa, and yet the factors shaping these variable associations among subgroup members have not been widely addressed. Associations may occur simply because of shared habitat preferences; however, social ties may also be influenced by genetic relatedness (kinship) or social attraction. Here, we investigate the association patterns of wild black-and-white ruffed lemurs,Varecia variegata, in Ranomafana National Park, Madagascar using behavioural, spatial (home range), and genetic data from twenty-four individually identified animals. We collected 40,840 records of group composition over a 17-month period and from this calculated pairwise association indices. We also used ranging coordinates and genetic samples to estimate patterns of spatial overlap and kinship, and then related these measures to patterns of affiliation. From these analyses, we found that dyadic ruffed lemur social associations were generally sparse and weak; that home range overlap was minimal; and that average relatedness within the community was low. We found no evidence that kinship was related to patterns of either spatial overlap or social association; instead, associations were primarily driven by space use. Moreover, social preferences were unrelated to kinship. While home range overlap explained most of the variation seen in social association, some variation remains unaccounted for, suggesting that other social, ecological, and biological factors such as shared resource defense or communal breeding might also play a role in social attraction. Our results further highlight the need to consider individual space use and nuances of species behavior when investigating social preference and social association more generally.
An anti-diuretic hormone receptor in the human disease vector,Aedes aegypti: identification, expression analysis and functional deorphanization
Authors: Sajadi Farwa , Uyuklu Ali , Paputsis Christine , Lajevardi Aryan , Wahedi Azizia , Ber Lindsay Taylor , Matei Andreea , Paluzzi Jean-Paul V. 
Published: October 2019

AbstractInsect CAPA neuropeptides, which are homologs of mammalian neuromedin U, have been described in various insect species and are known to influence ion and water balance by regulating the activity of the Malpighian ‘renal’ tubules (MTs). A number of diuretic hormones have been shown to increase primary fluid and ion secretion by the insect MTs and, in the adult female mosquito, a calcitonin-related peptide (DH31) also known as mosquito natriuretic peptide, increases sodium secretion at the expense of potassium to remove the excess salt load acquired upon blood-feeding. An endogenous mosquito anti-diuretic hormone was recently described, having inhibitory activity against select diuretic factors and being particularly potent against DH31-stimulated diuresis. In the present study, we have functionally deorphanized, bothin vitroandin vivo, a mosquito anti-diuretic hormone receptor (AedaeADHr). Expression analysis by quantitative PCR indicates the receptor is highly enriched in the MTs, and fluorescentin situhybridization confirms expression within principal cells. Characterization using a heterologous system demonstrated the receptor was highly sensitive to mosquito CAPA peptides. In adult females,AedaeADHr transcript knockdown using RNAi led to the abolishment of CAPA-peptide induced anti-diuretic control of DH31-stimulated MTs. The neuropeptidergic ligand is produced within a pair of neurosecretory cells in each of the six abdominal ganglia, whose axonal projections innervate the abdominal neurohaemal organs (known as the perivisceral organs), where these neurohormones are released into the open circulatory system of the insect. Furthermore, pharmacological inhibition of PKG/NOS signalling abolished the anti-diuretic activity ofAedaeCAPA-1, which collectively confirms the role of cGMP/PKG/NOS in this anti-diuretic signalling pathway.SignificanceInsects are by far the most successful and abundant group of organisms on earth. As a result of their small size, insects have a relatively large surface area to volume ratio, raising the potential for rapid gain or loss of water, ions and other molecules including toxins – a phenomenon that applies to insects living in both aquatic and terrestrial environments. In common with many other organisms, hormones are key regulators of the excretory system in insects, and numerous factors control the clearance of excess water and ions (i.e. diuretics) or retention of these elements (i.e. anti-diuretics). Here we characterized an endogenous anti-diuretic hormone receptor in the human disease vector,Aedes aegypti, demonstrating its expression is highly enriched in the Malpighian ‘renal’ tubules and is necessary for eliciting anti-diuretic control of this key component of the mosquito excretory system.
Improved prediction of MHC II antigen presentation through integration and motif deconvolution of mass spectrometry MHC eluted ligand data
Authors: Reynisson Birkir , Barra Carolina , Kaabinejadian Saghar , Hildebrand William H , Peters Bjoern , Nielsen Morten 
Published: October 2019

AbstractMajor Histocompatibility Complex II (MHC II) molecules play a vital role in the onset and control of cellular immunity. In a highly selective process, MHC II presents peptides derived from exogenous antigens on the surface of antigen-presenting cells for T cell scrutiny. Understanding the rules defining this presentation holds critical insights into the regulation and potential manipulation of the cellular immune system. Here, we apply the NNAlign_MA machine learning framework to analyse and integrate large-scale eluted MHC II ligand mass spectrometry (MS) data sets to advance prediction of CD4+ epitopes. NNAlign_MA allows integration of mixed data types, handling ligands with multiple potential allele annotations, encoding of ligand context, leveraging information between data sets, and has pan-specific power allowing accurate predictions outside the set of molecules included in the training data. Applying this framework, we identified accurate binding motifs of more than 50 MHC class II molecules described by MS data, particularly expanding coverage for DP and DQ beyond that obtained using current MS motif deconvolution techniques. Further, in large-scale benchmarking, the final model termed NetMHCIIpan-4.0, demonstrated improved performance beyond current state-of-the-art predictors for ligand and CD4+ T cell epitope prediction. These results suggest NNAlign_MA and NetMHCIIpan-4.0 are powerful tools for analysis of immunopeptidome MS data, prediction of T cell epitopes and development of personalized immunotherapies.
Ultrastructure of light-activated axons following optogenetic stimulation to produce late-phase long-term potentiation
Authors: Kuwajima Masaaki , Ostrovskaya Olga I. , Cao Guan , Weisberg Seth A. , Harris Kristen M. , Zemelman Boris V. 
Published: October 2019

AbstractAnalysis of neuronal compartments has revealed many state-dependent changes in geometry but establishing synapse-specific mechanisms at the nanoscale has proven elusive. We co-expressed channelrhodopsin2-GFP and mAPEX2 in a subset of hippocampal CA3 neurons and used trains of light to induce late-phase long-term potentiation (L-LTP) in area CA1. L-LTP was shown to be specific to the labeled axons by severing CA3 inputs, which prevented back-propagating recruitment of unlabeled axons. Membrane-associated mAPEX2 tolerated microwave-enhanced chemical fixation and drove tyramide signal amplification to deposit Alexa Fluor dyes in the light-activated axons. Subsequent post-embedding immunogold labeling resulted in outstanding ultrastructure and clear distinctions between labeled (activated), and unlabeled axons without obscuring subcellular organelles. The gold-labeled axons in potentiated slices were reconstructed through serial section electron microscopy; presynaptic vesicles and other constituents could be quantified unambiguously. The genetic specification, reliable physiology, and compatibility with established methods for ultrastructural preservation make this an ideal approach to link synapse ultrastructure and function in intact circuits.
Modeling a gene regulatory network of EMT hybrid states for mouse embryonic skin cells
Authors: Ramirez Dan , Kohar Vivek , Katebi Ataur , Lu Mingyang 
Published: October 2019

AbstractEpithelial-mesenchymal transition (EMT) plays a crucial role in embryonic development and tumorigenesis. Although EMT has been extensively studied with both computational and experimental methods, the gene regulatory mechanisms governing the transition are not yet well understood. Recent investigations have begun to better characterize the complex phenotypic plasticity underlying EMT using a computational systems biology approach. Here, we analyzed recently published single-cell RNA sequencing data from E9.5 to E11.5 mouse embryonic skin cells and identified the gene expression patterns of both epithelial and mesenchymal phenotypes, as well as a clear hybrid state. By integrating the scRNA-seq data and gene regulatory interactions from the literature, we constructed a gene regulatory network model governing the decision-making of EMT in the context of the developing mouse embryo. We simulated the network using a recently developed mathematical modeling method, named RACIPE, and observed three distinct phenotypic states whose gene expression patterns can be associated with the epithelial, hybrid, and mesenchymal states in the scRNA-seq data. Additionally, the model is in agreement with published results on the composition of EMT phenotypes and regulatory networks. We identified Wnt signaling as a major pathway in inducing the EMT and its role in driving cellular state transitions during embryonic development. Our findings demonstrate a new method of identifying and incorporating tissue-specific regulatory interactions into gene regulatory network modeling.Author SummaryEpithelial-mesenchymal transition (EMT) is a cellular process wherein cells become disconnected from their surroundings and acquire the ability to migrate through the body. EMT has been observed in biological contexts including development, wound healing, and cancer, yet the regulatory mechanisms underlying it are not well understood. Of particular interest is a purported hybrid state, in which cells can retain some adhesion to their surroundings but also show mesenchymal traits. Here, we examine the prevalence and composition of the hybrid state in the context of the embryonic mouse, integrating gene regulatory interactions from published experimental results as well as from the specific single cell RNA sequencing dataset of interest. Using mathematical modeling, we simulated a regulatory network based on these sources and aligned the simulated phenotypes with those in the data. We identified a hybrid EMT phenotype and revealed the inducing effect of Wnt signaling on EMT in this context. Our regulatory network construction process can be applied beyond EMT to illuminate the behavior of any biological phenomenon occurring in a specific context, allowing better identification of therapeutic targets and further research directions.
Predicting 3D genome folding from DNA sequence
Authors: Fudenberg Geoff , Kelley David R. , Pollard Katherine S. 
Published: October 2019

AbstractIn interphase, the human genome sequence folds in three dimensions into a rich variety of locus-specific contact patterns. Here we present a deep convolutional neural network, Akita, that accurately predicts genome folding from DNA sequence alone. Representations learned by Akita underscore the importance of CTCF and reveal a complex grammar underlying genome folding. Akita enables rapid in silico predictions for sequence mutagenesis, genome folding across species, and genetic variants.
A large inner membrane pore defines the ESX translocon
Authors: Poweleit Nicole , Czudnochowski Nadine , Nakagawa Rachael , Murphy Kenan , Sassetti Christopher , Rosenberg Oren S. 
Published: October 2019

AbstractThe ESX (or Type VII) secretion systems are protein export systems in mycobacteria and many Gram-positive bacteria that mediate a broad range of functions including virulence, conjugation, and metabolic regulation. These systems translocate folded dimers of WXG100-superfamily protein substrates across the cytoplasmic membrane; however, the architecture and mechanism of translocation has remained elusive. We report the cryo-electron microscopy structure of an ESX-3 system, purified using an epitope tag inserted with recombineering into the model organism Mycobacterium smegmatis. The structure reveals two large α-helical membrane pores of sufficient diameter to secrete folded substrates. A complex, asymmetric, multimeric cytoplasmic domain is poised to gate and regulate the pore’s function. Our study provides mechanistic insights into the ESX systems and will guide structure-based design of drugs targeting this unique bacterial translocon.One Sentence SummaryThe structure of the ESX-3 secretion system reveals a pore of sufficient size for the transit of folded substrates and a complex, cytoplasmic regulatory apparatus.
Impact of between-tissue differences on pan-cancer predictions of drug sensitivity
Authors: Lloyd John P. , Soellner Matthew , Merajver Sofia D. , Li Jun Z. 
Published: October 2019

ABSTRACTIncreased availability of drug response and genomics data for many tumor cell lines has accelerated the development of pan-cancer prediction models of drug response. However, it is unclear how much between-tissue differences in drug response and molecular characteristics may contribute to pan-cancer predictions. Also unknown is whether the performance of pan-cancer models could vary by cancer type. Here, we built a series of pan-cancer models using two datasets containing 346 and 504 cell lines with MEK inhibitor (MEKi) response and RNA, SNP, and CNV data, and found that, while the tissue-level drug responses are accurately predicted (between-tissue ρ=0.88-0.98), only 5 of 10 cancer types showed successful within-tissue prediction performance (within-tissue ρ=0.11-0.64). Between-tissue differences make substantial contributions to the performance of pan-cancer MEKi response predictions, as we estimate that exclusion of between-tissue signals leads to a 22% decrease in performance metrics. In practice, joint analysis of multiple cancer types usually has a larger sample size, hence greater power, than for one cancer type; and we observe that the higher accuracy of pan-cancer prediction of MEKi response is almost entirely due to the sample size advantage. Success of pan-cancer prediction reveals how drug response in different cancers may invoke shared regulatory mechanisms despite tissue-specific routes of oncogenesis, yet predictions in different cancer types require flexible incorporation of between-cancer and within-cancer signals. As most datasets in genome sciences contain multiple levels of heterogeneity, careful parsing of group characteristics and within-group, individual variation is essential when making robust inference.
Vaccine-specific immune responses againstMycobacterium ulceransinfection in a low-dose murine challenge model
Authors: Mangas Kirstie M. , Buultjens Andrew H. , Porter Jessica L. , Baines Sarah L. , Marion Estelle , Marsollier Laurent , Tobias Nicholas J. , Pidot Sacha J. , Quinn Kylie M. , Price David J. , Kedzierska Katherine , Zeng Weiguang , Jackson David C. , Chua Brendon Y. , Stinear Timothy P. 
Published: October 2019

AbstractThe neglected tropical disease Buruli ulcer (BU) is an infection of subcutaneous tissue withMycobacterium ulcerans. There is no effective BU vaccine. Here, we assessed an experimental prime-boost vaccine in a low-dose murine tail infection model. We used the enoyl-reductase (ER) domain of theM. ulceransmycolactone polyketide synthases electrostatically coupled with a previously described TLR-2 agonist-based lipopeptide adjuvant, R4Pam2Cys. Mice were vaccinated and then challenged via tail inoculation with 14-20 colony forming units (CFU) of an engineered bioluminescent strain ofM. ulcerans. Mice receiving either the experimental ER vaccine orMycobacterium bovisBacille Calmette-Guérin (BCG) were equally well protected, with both groups faring significantly better than non-vaccinated animals (p<0.05). A suite of 29 immune parameters were assessed in the mice at the end of the experimental period. Multivariate statistical approaches were then used to interrogate the immune response data to develop disease-prognostic models. High levels of IL-2 and low IFN-γproduced in the spleen best predicted control of infection across all vaccine groups. Univariate logistic regression then revealed vaccine-specific profiles of protection. High titres of ER-specific IgG serum antibodies together with IL-2 and IL-4 in the draining lymph node (DLN) were associated with protection induced by the experimental ER vaccine. In contrast, high titres of IL-6, TNF-α, IFN-γand IL-10 in the DLN and low IFNγtitres in the spleen were associated with protection following BCG vaccination. This study suggests an effective BU vaccine must induce localized, tissue-specific immune profiles with controlled inflammatory responses at the site of infection.
The interaction of aging and oxidative stress contributes to pathogenesis in mouse and human Huntington disease neurons
Authors: Machiela Emily , Jeloka Ritika , Caron Nicholas S. , Mehta Shagun , Schmidt Mandi E. , Tom Colton M. , Polturi Nalini , Xie Yuanyun , Mattis Virginia B , Hayden Michael R. , Southwell Amber L. 
Published: October 2019

AbstractHuntington disease (HD) is a fatal, inherited neurodegenerative disorder caused by a mutation in huntingtin (HTT). While mutant HTT is present ubiquitously throughout life, HD onset typically occurs in mid-life. Oxidative damage accumulates in the aging brain and is a feature of HD. We sought to interrogate the roles and interaction of age and oxidative stress in HD using primary Hu97/18 mouse neurons, neurons differentiated from HD patient induced pluripotent stem cells (iPSCs), and mice. We find that primary neurons must be matured in culture for canonical stress responses to occur. Furthermore, when aging is accelerated in mature HD neurons, mutant HTT accumulates and sensitivity to oxidative stress is selectively enhanced. Furthermore, we observe HD-specific phenotypes in iPSC-derived neurons and mouse brains that have undergone accelerated aging. These findings suggest a role for aging in HD pathogenesis and interaction between biological age of HD neurons and sensitivity to exogenous stress.