bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel antimicrobial alternative of microbiota metabolic product deoxycholic acid controls chicken necrotic enteritis
Authors: Wang Hong , Latorre Juan D. , Bansal Mohit , Al-Rubaye Bilal , Tellez Guillermo , Hargis Billy , Sun Xiaolun 
Published: February 2018

AbstractNecrotic enteritis (NE) caused by Clostridium perfringens infection has reemerged as a prevalent poultry disease worldwide due to reduced usage of prophylactic antibiotics. The lack of alternative antimicrobial strategies to control this disease is mainly due to limited insight into NE pathogenesis, microbiome relationships, and host responses. Here we reported that the metabolic byproduct of microbial metabolism of bile acids to deoxycholic acid (DCA), at as low as 50 μM, inhibited 82.8% of C. perfringens growth in Tryptic Soy Broth (P < 0.05). Sequential Eimeria maxima and C. perfringens challenge strongly induced NE, severe intestinal inflammation, and body weight (BW) loss in broiler chickens. These negative effects were diminished by 1.5 g/kg DCA diet. At the cellular level, DCA alleviated NE-associated ileal epithelial death and lamina propria immune cell apoptosis. Interestingly, DCA reduced C. perfringens invasion into villi without significantly altering the bacterial luminal colonization. Molecular analysis showed that DCA reduced inflammatory mediators of Infγ, Litaf (Tnfα), Il1β, and Mmp9 mRNA accumulation in ileal tissue. Mechanically, C. perfringens induced elevated expression of inflammatory cytokines of Infγ, Litaf, and Ptgs2 (COX-2 gene) in chicken splenocytes. Inhibiting the COX signaling by aspirin attenuated INFγ- or TNFa-induced inflammatory response in the splenocytes. Consistently, chickens fed 0.12 g/kg aspirin diet resisted against NE-induced BW loss, ileal inflammation, and villus apoptosis. In conclusion, microbial metabolic product DCA prevents NE-induced BW loss and ileal inflammation through curbing inflammatory response. These novel findings could serve as a stepping-stone for developing next generation antimicrobial alternatives against NE.
CD117/c-kit in Cancer Stem Cell-Mediated Progression and Therapeutic Resistance
Authors: Foster Brittni M. , Zaidi Danish , Young Tyler R. , Mobley Mary E. , Kerr Bethany A. 
Published: February 2018

ABSTRACTMetastasis is the primary cause of cancer patient morbidity and mortality but due to persisting gaps in our knowledge, it remains untreatable. Metastases often occur as patients' tumors progress or recur after initial therapy. Tumor recurrence at the primary site may be driven by a cancer stem-like cell or tumor progenitor cell, while recurrence at a secondary site is driven by metastatic cancer stem cells or metastasis-initiating cells. Ongoing efforts are aimed at identifying and characterizing these stem-like cells driving recurrence and metastasis. One potential marker for the cancer stem-like cell subpopulation is CD117/c-kit, a tyrosine kinase receptor associated with cancer progression and normal stem cell maintenance. In our analyses, CD117 was expressed in several tissues and was highly expressed in bone marrow progenitor cells. Also, we uncovered that CD117 gene amplifications and mutations occurred in multiple cancers. Further, activation of CD117 by its ligand stem cell factor (SCF; kit ligand) in the progenitor cell niche stimulates several signaling pathways driving proliferation, survival, and migration. These signaling pathways were commonly altered in patients with CD117 amplifications and mutations. Here, we examine evidence that the SCF/CD117 signaling axis controls cancer progression through the regulation of stemness and resistance to tyrosine kinase inhibitors.AbbreviationsAMLacute myeloid leukemiaCMLchronic myeloid leukemiaCTCcirculating tumor cellCSCcancer stem cellDTCdisseminated tumor cellGISTgastrointestinal stromal tumorHSChematopoietic stem cellSCFstem cell factorTKItyrosine kinase inhibitor
Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences1
Authors: Linnér Richard Karlsson , Biroli Pietro , Kong Edward , Meddens S Fleur W , Wedow Robbee , Fontana Mark Alan , Lebreton Maël , Abdellaoui Abdel , Hammerschlag Anke R , Nivard Michel G , Okbay Aysu , Rietveld Cornelius A , Timshel Pascal N , Tino Stephen P , Trzaskowski Maciej , Vlaming Ronald de , Zünd Christian L , Bao Yanchun , Buzdugan Laura , Caplin Ann H , Chen Chia-Yen , Eibich Peter , Fontanillas Pierre , Gonzalez Juan R , Joshi Peter K , Karhunen Ville , Kleinman Aaron , Levin Remy Z , Lill Christina M , Meddens Gerardus A , Muntané Gerard , Sanchez-Roige Sandra , Rooij Frank J van , Taskesen Erdogan , Wu Yang , Zhang Futao ,   23andMe Research Team, eQTLgen Consortium, International Cannabis Consortium, Psychiatric Genomics Consortium, Social Science Genetic Association Consortium,, Auton Adam , Boardman Jason D , Clark David W , Conlin Andrew , Dolan Conor C , Fischbacher Urs , Groenen Patrick JF , Harris Kathleen Mullan , Hasler Gregor , Hofman Albert , Ikram Mohammad A , Jain Sonia , Karlsson Robert , Kessler Ronald C , Kooyman Maarten , MacKillop James , Männikkö Minna , Morcillo-Suarez Carlos , McQueen Matthew B , Schmidt Klaus M , Smart Melissa C , Sutter Matthias , Thurik A Roy , Uitterlinden Andre G , White Jon , Wit Harriet de , Yang Jian , Bertram Lars , Boomsma Dorret , Esko Tõnu , Fehr Ernst , Hinds David A , Johannesson Magnus , Kumari Meena , Laibson David , Magnusson Patrik KE , Meyer Michelle N , Navarro Arcadi , Palmer Abraham A , Pers Tune H , Posthuma Danielle , Schunk Daniel , Stein Murray B , Svento Rauli , Tiemeier Henning , Timmers Paul RHJ , Turley Patrick , Ursano Robert J , Wagner Gert G , Wilson James F , Gratten Jacob , Lee James J , Cesarini David , Benjamin Daniel J , Koellinger Philipp D , Beauchamp Jonathan P 
Published: February 2018

AbstractHumans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 approximately independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to strongly genetically correlated (to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated SNPs are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We find no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.
hts-nim: scripting high-performance genomic analyses
Authors: Pedersen Brent S. , Quinlan Aaron R. 
Published: February 2018

AbstractMotivationExtracting biological insight from genomic data inevitably requires custom software. In many cases, this is accomplished with scripting languages, owing to their accessibility and brevity. Unfortunately, the ease of scripting languages typically comes at a substantial performance cost that is especially acute with the scale of modern genomics datasets.ResultsWe present hts-nim, a high-performance library written in the Nim programming language that provides a simple, scripting-like syntax without sacrificing performance.Availabilityhts-nim is available at https://github.com/brentp/hts-nim and the example tools are at https://github.com/brentp/hts-nim-tools both under the MIT license.Contactbpederse@gmail.comSupplementary informationSupplementary data are available at Bioinformatics online.
Improving Metagenomic Assemblies Through Data Partitioning: a GC content approach
Authors: Miranda Fábio , Batista Cassio , Silva Artur , Morais Jefferson , Neto Nelson , Ramos Rommel 
Published: February 2018

AbstractAssembling metagenomic data sequenced by NGS platforms poses significant computational challenges, especially due to large volumes of data, sequencing errors, and variations in size, complexity, diversity and abundance of organisms present in a given metagenome. To overcome these problems, this work proposes an open-source, bioinfor-matic tool called GCSplit, which partitions metagenomic sequences into subsets using a computationally inexpensive metric: the GC content. Experiments performed on real data show that preprocessing short reads with GCSplit prior to assembly reduces memory consumption and generates higher quality results, such as an increase in the N50 metric and the reduction in both the L50 value and the total number of contigs produced in the assembly. GCSplit is available at https://github.com/mirand863/gcsplit.
Example of Methylome Analysis with MethylIT using Cancer Datasets
Authors: Sanchez Robersy , Mackenzie Sally 
Published: February 2018

AbstractMethyl-IT, a novel methylome analysis procedure based on information thermodynamics and signal detection was recently released. Methylation analysis involves a signal detection problem, and the method was designed to discriminate methylation regulatory signal from background noise induced by thermal fluctuations. Methyl-IT enhances the resolution of genome methylation behavior to reveal network-associated responses, offering resolution of gene pathway influences not attainable with previous methods. Herein, an example of MethylIT application to the analysis of breast cancer methylomes is presented.
Co-occurrence history increases ecosystem temporal stability and recovery from a flood in experimental plant communities
Authors: van Moorsel Sofia J. , Hahl Terhi , Petchey Owen L. , Ebeling Anne , Eisenhauer Nico , Schmid Bernhard , Wagg Cameron 
Published: February 2018

AbstractUnderstanding factors that increase ecosystem stability is critical in the face of environmental change. Experiments simulating species loss from grassland ecosystems have shown that losing biodiversity decreases the ability of ecosystems to buffer negative effects of disturbances. However, as the originally sown experimental communities with reduced biodiversity develop, plant evolutionary processes or the assembly of interacting soil organisms may allow them to develop stability and resilience over time. We explored such effects in a long-term grassland biodiversity experiment with plant communities with either a history of co-occurrence (selected communities) or no such history (naïve communities) over a four-year period in which a major flood disturbance occurred.We found selected communities had temporally more stable biomass than the same communities of naïve plants, especially at low species richness. Furthermore, selected communities showed greater short-term biomass recovery after flooding, resulting in more stable post-flood productivity. In contrast to a previous study, the positive diversity–stability relationship was maintained after the flooding. Our results were consistent across three soil treatments simulating the presence or absence of co-selected microbial communities. We suggest that prolonged exposure of plant populations to a particular community context and abiotic site conditions can increase ecosystem temporal stability and resistance to disturbance. We argue that selection during the course of a biodiversity experiment is the most parsimonious explanation for these effects. A history of co-occurrence can in part compensate for species loss, as can high plant diversity in part compensate for the missing opportunity of such adaptive adjustments.
Mycobacterium tuberculosis-specific CD4+and CD8+T cells differ in their capacity to recognize infected macrophages
Authors: Yang Jason , Mott Daniel , Sutiwisesak Rujapak , Lu Yu Jung , Raso Fiona , Stowell Britni , Babunovic Greg , Lee Jinhee , Carpenter Steve , Way Sing Sing , Fortune Sarah , Behar Sam 
Published: February 2018

AbstractContainment ofMycobacterium tuberculosis(Mtb) infection requires T cell recognition of infected macrophages. Mtb has evolved to tolerate, evade, and subvert host immunity. Despite a vigorous and sustained CD8+T cell response during Mtb infection, CD8+T cells make limited contribution to protection. Here, we ask whether the ability of Mtb-specific T cells to restrict Mtb growth is related to their capacity to recognize Mtb-infected macrophages.We derived CD8+T cell lines that recognized the Mtb immunodominant epitope TB10.44-11and compared them to CD4+T cell lines that recognized Ag85b240-254 or ESAT63-17. While the CD4+T cells recognized Mtb-infected macrophages and inhibited Mtb growth in vitro, the TB10.4-specific CD8+T cells neither recognized Mtb-infected macrophages nor restricted Mtb growth. TB10.4-specific CD8+T cells recognized macrophages infected withListeria monocytogenesexpressing TB10.4. However, over-expression of TB10.4 in Mtb did not confer recognition by TB10.4-specific CD8+T cells. Importantly, CD8+T cells recognized macrophages pulsed with irradiated Mtb, indicating that macrophages can efficiently cross-present the TB10.4 protein and raising the possibility that viable bacilli might suppress cross-presentation. Importantly, polyclonal CD8+T cells specific for Mtb antigens other than TB10.4 recognized Mtb-infected macrophages in a MHC-restricted manner.As TB10.4 elicits a dominant CD8+T cell response that poorly recognizes Mtb-infected macrophages, we propose that TB10.4 acts as a decoy antigen. Moreover, it appears that this response overshadows subdominant CD8+T cell response that can recognize Mtb-infected macrophages. The ability of Mtb to subvert the CD8+T cell response may explain why CD8+T cells make a disproportionately small contribution to host defense compared to CD4+T cells. The selection of Mtb antigens for vaccines has focused on antigens that generate immunodominant responses. We propose that establishing whether vaccine-elicited, Mtb-specific T cells recognize Mtb-infected macrophages could be a useful criterion for preclinical vaccine development.
Generative adversarial networks simulate gene expression and predict perturbations in single cells
Authors: Ghahramani Arsham , Watt Fiona M. , Luscombe Nicholas M. 
Published: February 2018

AbstractRecent advances have enabled gene expression profiling of single cells at lower cost. As more data is produced there is an increasing need to integrate diverse datasets and better analyse underutilised data to gain biological insights. However, analysis of single cell RNA-seq data is challenging due to biological and technical noise which not only varies between laboratories but also between batches. Here for the first time, we apply a new generative deep learning approach called Generative Adversarial Networks (GAN) to biological data. We apply GANs to epidermal, neural and hematopoietic scRNA-seq data spanning different labs and experimental protocols. We show that it is possible to integrate diverse scRNA-seq datasets and in doing so, our generative model is able to simulate realistic scRNA-seq data that covers the full diversity of cell types. In contrast to many machine-learning approaches, we are able to interpret internal parameters in a biologically meaningful manner. Using our generative model we are able to obtain a universal representation of epidermal differentiation and use this to predict the effect of cell state perturbations on gene expression at high time-resolution. We show that our trained neural networks identify biological state-determining genes and through analysis of these networks we can obtain inferred gene regulatory relationships. Finally, we use internal GAN learned features to perform dimensionality reduction. In combination these attributes provide a powerful framework to progress the analysis of scRNA-seq data beyond exploratory analysis of cell clusters and towards integration of multiple datasets regardless of origin.
Shared Nucleotide Flanks Confer Transcriptional Competency to bZip Core Motifs
Authors: Cohen Daniel M. , Lim Hee-Woong , Won Kyoung-Jae , Steger David J. 
Published: February 2018

ABSTRACTSequence-specific DNA binding recruits transcription factors (TFs) to the genome to regulate gene expression. Here, we perform high resolution mapping of CEBP proteins to determine how sequence dictates genomic occupancy. We demonstrate a fundamental difference between the sequence repertoire utilized by CEBPs in vivo versus the palindromic sequence preference reported by classical in vitro models, by identifying a palindromic motif at less than 1% of the genomic binding sites. On the native genome, CEBPs bind a diversity of related 10 bp sequences resulting from the fusion of degenerate and canonical half-sites. Altered DNA specificity of CEBPs in cells occurs through heterodimerization with other bZip TFs, and approximately 40% of CEBP-binding sites in primary human cells harbor motifs characteristic of CEBP heterodimers. In addition, we uncover an important role for sequence bias at core-motif-flanking bases for CEBPs and demonstrate that flanking bases regulate motif function across mammalian bZip TFs. Favorable flanking bases confer efficient TF occupancy and transcriptional activity, and DNA shape may explain how the flanks alter TF binding. Importantly, motif optimization within the 10-mer is strongly correlated with cell-type-independent recruitment of CEBPβ, providing key insight into how sequence sub-optimization affects genomic occupancy of widely expressed CEBPs across cell types.
Effect of environment on the evolutionary trajectories and growth characteristics of antibiotic-resistant Escherichia coli mutants
Authors: Hubbard Alasdair T. M. , Jafari Nazila V. , Feasey Nicholas , Rohn Jennifer L. , Roberts Adam P. 
Published: February 2018

AbstractIn the face of an accelerating global antimicrobial resistance crisis, the determination of bacterial fitness following acquisition of resistance is an expanding area of research, and increased understanding of this process will be crucial to translate in vitro fitness data to successful therapies. Given that crucial clinical treatment situations are guided by in vitro diagnostic testing in an artificial environment far removed from human physiological niches, we used Escherichia coli and amoxicillin-clavulanic acid (AMC) resistance as a model to understand how such environments could affect the emergence of resistance, associated fitness costs and the predictive value of this data when strains were grown in the more physiologically relevant environments of urine and urothelial organoids. Resistant E. coli isolates were selected for following 24-hour exposure to sub-inhibitory concentrations of AMC in either M9, ISO or LB broth, followed by growth on LB agar containing AMC. No resistant colonies emerged following growth in M9, whereas resistant isolates were detected from cultures grown in ISO and LB broth. We observed both within and between media-type variability in the levels of resistance and fitness of the resistant mutants grown in LB. MICs and fitness of these resistant strains in different media (M9, ISO, LB, human urine and urothelial organoids) showed considerable variation. Media can therefore have a direct effect on the isolation of mutants that confer resistance to AMC and these mutants can exhibit unpredictable MIC and fitness profiles under different growth conditions. This study highlights the risks in relying on a single culture protocol to predict the behaviour and treatment response of bacteria in vivo and highlights the importance of developing comprehensive experimental designs to ensure effective translation of diagnostic procedures to successful clinical outcomes.
First nuclear genome assembly of an extinct moa species, the little bush moa (Anomalopteryx didiformis)
Authors: Cloutier Alison , Sackton Timothy B. , Grayson Phil , Edwards Scott V. , Baker Allan J. 
Published: February 2018

AbstractHigh throughput sequencing (HTS) has revolutionized the field of ancient DNA (aDNA) by facilitating recovery of nuclear DNA for greater inference of evolutionary processes in extinct species than is possible from mitochondrial DNA alone. We used HTS to obtain ancient DNA from the little bush moa (Anomalopteryx didiformis), one of the iconic species of large, flightless birds that became extinct following human settlement of New Zealand in the 13 th century. In addition to a complete mitochondrial genome at 249.9X depth of coverage, we recover almost 900 Mb of the moa nuclear genome by mapping reads to a high quality reference genome for the emu (Dromaius novaehollandiae). This first nuclear genome assembly for moa covers approximately 75% of the 1.2 Gb emu reference with sequence contiguity sufficient to identify more than 85% of bird universal single-copy orthologs. From this assembly, we isolate 40 polymorphic microsatellites to serve as a community resource for future population-level studies in moa. We also compile data for a suite of candidate genes associated with vertebrate limb development and show that the wingless moa phenotype is likely not attributable to gene loss or pseudogenization among this candidate set. We also identify potential function-altering coding sequence variants in moa for future experimental assays.
DNA methylation dynamics during embryonic development and postnatal maturation of the mouse auditory organ of Corti
Authors: Yizhar-Barnea Ofer , Valensisi Cristina , Kishore Kamal , Doni Jayavelu Naresh , Andrus Colin , Koffler-Brill Tal , Ushakov Kathy , Perl Kobi , Noy Yael , Bhonker Yoni , Pelizzola Mattia , Hawkins R. David , Avraham Karen B. 
Published: February 2018

AbstractBackgroundThe mammalian inner ear is a complex morphological structure responsible for hearing and balance, and its pathology is associated with deafness and balance disorders. To evaluate the role of epigenomic dynamics in the development and maturation of mouse inner ear sensory epithelium, we performed whole-genome bisulfite sequencing on inner ear tissue, yielding temporal base-pair resolution methylomes at key developmental time points.ResultsWe found a late accumulation of non-CpG methylation, indicating a similarity between the inner ear sensory epithelium and neuronal tissue. Moreover, annotation of both unmethylated and low methylated regions pointed to regulatory elements active in the inner ear in proximity of and distal from transcriptional units. Finally, we identified differentially methylated regions across the transition periods. An analysis of these regions led us to identify several novel candidate regulatory factors, connecting regulatory elements from specific time points in development to molecular features that drive the development and maturation of the inner ear sensory epithelium. The GJB6 locus putative regulatory region was shown to upregulate distal GJB6 gene expression and a non-coding RNA.ConclusionsOur analysis of inner ear sensory epithelium DNA methylation sheds light on novel regulatory regions in the hearing organ, and may help boost diagnostic capabilities and guide the development of therapeutics for hearing loss, by providing multiple intervention points for manipulation of the auditory system.