bluuebunny/crossref_metadata_2025_split huggingface dataset:
Zika virus as a sexually transmitted pathogen
Authors: Mead Paul S. , Hills Susan L. , Brooks John T. 
Published: November 2017

Purpose of review
Zika virus has recently emerged from an obscure mosquito-borne pathogen to an international public health concern. It is the first viral agent newly demonstrated to cause birth defects in several decades, and it is the only arbovirus now known to be transmitted sexually. The purpose of this review is to provide an overview of current understanding of sexual transmission of Zika virus and its possible clinical and public health consequences.

Recent findings
Sexual transmission of Zika virus has been reported from at least 13 countries without simultaneous mosquito-borne transmission; it is undoubtedly also occurring in countries with active arthropod transmission. Most published cases involve transmission from symptomatically infected men to women partners. Nevertheless, transmission from a symptomatic man to another man, from a symptomatic woman to a man, and from an asymptomatic man to a woman has also been reported. Sexual transmission has occurred before symptom onset, during illness, and after resolution of the source partner's symptoms. With the exception of a woman who developed symptomatic infection 44 days after onset of her husband's illness, nearly all instances reported to date have occurred within 20 days of the source partner's illness. Zika virus RNA has been detected in semen, saliva, blood, urine, and vaginal and cervical secretions; the length of time during which RNA can be detected varies widely across different body fluids but is especially lengthy in semen. Although semen has been found to contain ZIKV RNA for more than 180 days after illness onset, only a small proportion of samples with detectable RNA yield replicative virus whenever cultured.

Summary
Public health agencies have promulgated interim recommendations to prevent sexual transmission of Zika virus; however, much remains unknown regarding the duration of contagiousness and risk factors for transmission. Given the risk for birth defects, the greatest concern is for transmission of the virus to women who are pregnant or attempting to become pregnant. To prevent sexual transmission in general, couples are advised to use condoms or not have sex for at least 6 months from the start of the male partner's symptoms or the date he was diagnosed with Zika or after he has returned from an area with risk of ZIKV infection. Women who have symptomatic ZIKV infection or have traveled to an area of risk are advised to use condoms or avoid sex for 8 weeks from the start of the woman's symptoms or the date she was diagnosed with Zika or after the woman returns from the area of risk.
Scaling accurate genetic variant discovery to tens of thousands of samples
Authors: Poplin Ryan , Ruano-Rubio Valentin , DePristo Mark A. , Fennell Tim J. , Carneiro Mauricio O. , Van der Auwera Geraldine A. , Kling David E. , Gauthier Laura D. , Levy-Moonshine Ami , Roazen David , Shakir Khalid , Thibault Joel , Chandran Sheila , Whelan Chris , Lek Monkol , Gabriel Stacey , Daly Mark J , Neale Ben , MacArthur Daniel G. , Banks Eric 
Published: November 2017

AbstractComprehensive disease gene discovery in both common and rare diseases will require the efficient and accurate detection of all classes of genetic variation across tens to hundreds of thousands of human samples. We describe here a novel assembly-based approach to variant calling, the GATK HaplotypeCaller (HC) and Reference Confidence Model (RCM), that determines genotype likelihoods independently per-sample but performs joint calling across all samples within a project simultaneously. We show by calling over 90,000 samples from the Exome Aggregation Consortium (ExAC) that, in contrast to other algorithms, the HC-RCM scales efficiently to very large sample sizes without loss in accuracy; and that the accuracy of indel variant calling is superior in comparison to other algorithms. More importantly, the HC-RCM produces a fully squared-off matrix of genotypes across all samples at every genomic position being investigated. The HC-RCM is a novel, scalable, assembly-based algorithm with abundant applications for population genetics and clinical studies.
Combined flow cytometry and high throughput image analysis for the study of essential genes in Caenorhabditis elegans
Authors: Hernando-Rodríguez Blanca , Erinjeri Annmary Paul , Rodríguez-Palero María Jesús , Millar Val , González-Hernández Sara , Olmedo María , Schulze Bettina , Baumeister Ralf , Muñoz Manuel J. , Askjaer Peter , Artal-Sanz Marta 
Published: November 2017

ABSTRACTBackgroundThe advancement in automated image based microscopy platforms coupled with high throughput liquid workflows has facilitated the design of large scale screens utilizing multicellular model organisms such as Caenorhabditis elegans to identify genetic interactions, therapeutic drugs or disease modifiers. However, the analysis of essential genes has lagged behind because lethal or sterile mutations pose a bottleneck for high throughput approaches.ResultsIn C. elegans, non-conditional lethal mutations can be maintained in heterozygosis using chromosome balancers, commonly labelled with GFP in the pharynx. Moreover gene-expression is typically monitored by the use of fluorescent reporters marked with the same fluorophore. Therefore, the separation of the different populations of animals at early larval stages represents a challenge. Here, we develop a sorting strategy capable of selecting homozygous mutants carrying a GFP stress reporter from GFP-balanced animals at early larval stages. Because sorting is not completely error-free, we develop an automated high-throughput image-analysis protocol that identifies and discards animals carrying the chromosome balancer. We demonstrate the experimental usefulness of combining sorting of homozygous lethal mutants and automated image-analysis in a functional genomic RNAi screen for genes that genetically interact with mitochondrial prohibitin (PHB). Lack of PHB results in embryonic lethality, while, homozygous PHB deletion mutants develop into sterile adults due to maternal contribution and strongly induce the mitochondrial unfolded protein response (UPRmt). In a chromosome-wide RNAi screen for C. elegans genes having human orthologues, we uncover both, known and new PHB genetic interactors affecting the UPRmt and growth.ConclusionsA systematic way to analyse genetic interactions of essential genes in multicellular organisms is lacking. The method presented here allows the study of balanced lethal mutations in a high-throughput manner and can be easily adapted depending on the user’s requirements. Therefore, it will serve as a useful resource for the C. elegans community for probing new biological aspects of essential nematode genes as well as the generation of more comprehensive genetic networks.
A systems approach to refine disease taxonomy by integrating phenotypic and molecular networks
Authors: Zhou Xuezhong , Lei Lei , Liu Jun , Halu Arda , Zhang Yingying , Li Bing , Guo Zhili , Liu Guangming , Sun Changkai , Loscalzo Joseph , Sharma Amitabh , Wang Zhong 
Published: November 2017

SummaryThe International Classification of Diseases (ICD) relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in ICD should be further investigated. Here, we propose a new classification of diseases (NCD) by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles. With statistical validations from phenotype-genotype associations and interactome networks, we demonstrate that NCD improves disease specificity owing to its overlapping categories and polyhierarchical structure. Furthermore, NCD captures the molecular diversity of diseases and defines clearer boundaries in terms of both phenotypic similarity and molecular associations, establishing a rational strategy to reform disease taxonomy.
Structure and function of accessory Sec proteins involved in the adhesin export pathway of Streptococcus gordonii
Authors: Chen Yu , Bensing Barbara A. , Seepersaud Ravin , Mi Wei , Liao Maofu , Jeffrey Philip D. , Shajahan Asif , Sonon Roberto N. , Azadi Parastoo , Sullam Paul M. , Rapoport Tom A. 
Published: November 2017

ABSTRACTMany pathogenic bacteria, includingStreptococcus gordonii, possess a pathway for the export of a single serine-rich-repeat protein that mediates the adhesion of bacteria to host cells and the extracellular matrix. These adhesins areO-glycosylated by several cytosolic glycosyltransferases and require three accessory Sec proteins (Asp1-3) for export, but how the adhesins are processed for secretion is not well defined. Here, we show thatO-glycosylation ofS. gordoniiadhesin GspB occurs in a sequential manner by three enzymes (GtfA/B, Nss, Gly) that attach N-acetylglucosamine and glucose to Ser/Thr residues. The modified substrate is subsequently transferred from the last glycosyltransferase to the Asp1/2/3 complex. Crystal structures show that both Asp1 and Asp3 are related to carbohydrate binding proteins. Asp1 also has an affinity for phospholipids, which is attenuated by Asp2. These results suggest a mechanism for the modification of adhesin in the cytosol and its subsequent targeting to the export machinery.
Discrete and continuum approximations for collective cell migration in a scratch assay with cell size dynamics
Authors: Matsiaka Oleksii M , Penington Catherine J , Baker Ruth E , Simpson Matthew J 
Published: November 2017

AbstractScratch assays are routinely used to study the collective spreading of cell populations. In general, the rate at which a population of cells spreads is driven by the combined effects of cell migration and proliferation. To examine the effects of cell migration separately from the effects of cell proliferation, scratch assays are often performed after treating the cells with a drug that inhibits proliferation. Mitomycin-C is a drug that is commonly used to suppress cell proliferation in this context. However, in addition to suppressing cell proliferation, Mitomycin-C also causes cells to change size during the experiment, as each cell in the population approximately doubles in size as a result of treatment. Therefore, to describe a scratch assay that incorporates the effects of cell-to-cell crowding, cell-to-cell adhesion, and dynamic changes in cell size, we present a new stochastic model that incorporates these mechanisms. Our agent-based stochastic model takes the form of a system of Langevin equations that is the system of stochastic differential equations governing the evolution of the population of agents. We incorporate a time-dependent interaction force that is used to mimic the dynamic increase in size of the agents. To provide a mathematical description of the average behaviour of the stochastic model we present continuum limit descriptions using both a standard mean-field approximation, and a more sophisticated moment dynamics approximation that accounts for the density of agents and density of pairs of agents in the stochastic model. Comparing the accuracy of the two continuum descriptions for a typical scratch assay geometry shows that the incorporation of agent growth in the system is associated with a decrease in accuracy of the standard mean-field description. In contrast, the moment dynamics description provides a more accurate prediction of the evolution of the scratch assay when the increase in size of individual agents is included in the model.
The nature of nurture: effects of parental genotypes
Authors: Kong Augustine , Thorleifsson Gudmar , Frigge Michael L. , Vilhjálmsson Bjarni J. , Young Alexander I. , Thorgeirsson Thorgeir E. , Benonisdottir Stefania , Oddsson Asmundur , Halldórsson Bjarni V. , Masson Gísli , Gudbjartsson Daniel F. , Helgason Agnar , Bjornsdottir Gyda , Thorsteinsdottir Unnur , Stefansson Kari 
Published: November 2017

AbstractSequence variants in the parental genomes that are not transmitted to a child/proband are often ignored in genetic studies. Here we show that non-transmitted alleles can impact a child through their effects on the parents and other relatives, a phenomenon we call genetic nurture. Using results from a meta-analysis of educational attainment, the polygenic score computed for the non-transmitted alleles of 21,637 probands with at least one parent genotyped has an estimated effect on the educational attainment of the proband that is 29.9% (P= 1.6×10−14) of that of the transmitted polygenic score. Genetic nurturing effects of this polygenic score extend to other traits. Paternal and maternal polygenic scores have similar effects on educational attainment, but mothers contribute more than fathers to nutrition/heath related traits.One Sentence SummaryNurture has a genetic component,i.e.alleles in the parents affect the parents’ phenotypes and through that influence the outcomes of the child.
Combining RNA-seq data and homology-based gene prediction for plants, animals and fungi
Authors: Keilwagen Jens , Hartung Frank , Paulini Michael , Twardziok Sven O. , Grau Jan 
Published: November 2017

MotivationGenome annotation is of key importance in many research questions. The identification of protein-coding genes is often based on transcriptome sequencing data, ab-initio or homology-based prediction. Recently, it was demonstrated that intron position conservation improves homology-based gene prediction, and that experimental data improves ab-initio gene prediction.ResultsHere, we present an extension of the gene prediction tool GeMoMa that utilizes amino acid sequence conservation, intron position conservation and optionally RNA-seq data for homology-based gene prediction. We show on published benchmark data for plants, animals and fungi that GeMoMa performs better than the gene prediction programs BRAKER1, MAKER2, and CodingQuarry, and purely RNA-seq-based pipelines for transcript identification. In addition, we demonstrate that using multiple reference organisms may help to further improve the performance of GeMoMa. Finally, we apply GeMoMa to four nematode species and to the recently published barley reference genome indicating that current annotations of protein-coding genes may be refined using GeMoMa predictions.AvailabilityGeMoMa has been published under GNU GPL3 and is freely available at http://www.jstacs.de/index.php/GeMoMa.Contactjens.keilwagen@julius-kuehn.de
Potent and Selective Antitumor Activity of a T-Cell Engaging Bispecific Antibody Targeting a Membrane-Proximal Epitope of ROR1
Authors: Qi Junpeng , Li Xiuling , Peng Haiyong , Park HaJeung , Rader Christoph 
Published: November 2017

AbstractT-cell engaging bispecific antibodies present a promising strategy for cancer immunotherapy and numerous bispecific formats have been developed for retargeting cytolytic T cells toward tumor cells. To explore the therapeutic utility of T-cell engaging bispecific antibodies targeting the receptor tyrosine kinase ROR1, which is expressed by tumor cells of various hematologic and solid malignancies, we used a bispecific ROR1 × CD3 scFv-Fc format based on a heterodimeric and aglycosylated Fc domain designed for extended circulatory half-life and diminished systemic T-cell activation. A diverse panel of ROR1-targeting scFv derived from immune and naïve rabbit antibody repertoires was compared in this bispecific format for target-dependent T-cell recruitment and activation. A ROR1-targeting scFv with a membrane-proximal epitope, R11, revealed potent and selective antitumor activityin vitroandin vivoand emerged as a prime candidate for further preclinical and clinical studies. To elucidate the precise location and engagement of this membrane-proximal epitope, which is conserved between human and mouse ROR1, the three-dimensional structure of scFv R11 in complex with the kringle domain of ROR1 was determined by X-ray crystallography at 1.6-Å resolution.
Cross-species systems analysis of evolutionary toolkits of neurogenomic response to social challenge
Authors: Saul Michael C. , Blatti Charles , Yang Wei , Bukhari Syed Abbas , Shpigler Hagai Y. , Troy Joseph M. , Seward Christopher H. , Sloofman Laura , Chandrasekaran Sriram , Bell Alison M. , Stubbs Lisa , Robinson Gene E. , Zhao Sihai Dave , Sinha Saurabh 
Published: November 2017

ABSTRACTSocial challenges like territorial intrusions evoke behavioral responses in widely diverging species. Recent work has revealed that evolutionary “toolkits” – genes and modules with lineage-specific variations but deep conservation of function – participate in the behavioral response to social challenge. Here, we develop a multi-species computational-experimental approach to characterize such a toolkit at a systems level. Brain transcriptomic responses to social challenge was probed via RNA-seq profiling in three diverged species – honey bees, mice, and three-spined stickleback fish – following a common methodology, allowing fair comparisons across species. Data were collected from multiple brain regions and multiple time points after social challenge exposure, achieving anatomical and temporal resolution substantially greater than previous work. We developed statistically rigorous analyses equipped to find homologous functional groups among these species at the levels of individual genes, functional and coexpressed gene modules, and transcription factor sub-networks. We identified six orthogroups involved in response to social challenge, including groups represented by mouse genes Npas4 and Nr4a1, as well as common modulation of systems such as transcriptional regulators, ion channels, G-protein coupled receptors, and synaptic proteins. We also identified conserved coexpression modules enriched for mitochondrial fatty acid metabolism and heat shock that constitute the shared neurogenomic response. Our analysis suggests a toolkit wherein nuclear receptors, interacting with chaperones, induce transcriptional changes in mitochondrial activity, neural cytoarchitecture, and synaptic transmission after social challenge. It reveals systems-level mechanisms that have been repeatedly co-opted during evolution of analogous behaviors, thus advancing the genetic toolkit concept beyond individual genes.
Genetic Single Neuron Anatomy reveals fine granularity of cortical interneuron subtypes
Authors: Wang Xiaojun , Tucciarone Jason , Jiang Siqi , Yin Fangfang , Wang Bor-shuen , Wang Dingkang , Jia Yao , Jia Xueyan , Li Yuxin , Yang Tao , Xu Zhengchao , Akram Masood A. , Wang Yusu , Zeng Shaoqun , Ascoli Giorgio A. , Mitra Partha , Gong Hui , Luo Qingming , Huang Z. Josh 
Published: November 2017

AbstractParsing diverse nerve cells into biological types is necessary for understanding neural circuit organization. Morphology is an intuitive criterion for neuronal classification and a proxy of connectivity, but morphological diversity and variability often preclude resolving the granularity of discrete cell groups from population continuum. Combining genetic labeling with high-resolution, large volume light microscopy, we established a platform of genetic single neuron anatomy that resolves, registers and quantifies complete neuron morphologies in the mouse brain. We discovered that cortical axo-axonic cells (AACs), a cardinal GABAergic interneuron type that controls pyramidal neuron (PyN) spiking at axon initial segment, consist of multiple subtypes distinguished by laminar position, dendritic and axonal arborization patterns. Whereas the laminar arrangements of AAC dendrites reflect differential recruitment by input streams, the laminar distribution and local geometry of AAC axons enable differential innervation of PyN ensembles. Therefore, interneuron types likely consist of fine-grained subtypes with distinct input-output connectivity patterns.
High-throughput sequencing of murine immunoglobulin heavy chain transcripts using single side unique molecular identifiers on an Ion Torrent PGM
Authors: Bürckert Jean-Philippe , Faison William J. , Dubois Axel R. S. X. , Sinner Regina , Hunewald Oliver , Wienecke-Baldacchino Anke , Brieger Anne , Muller Claude P. 
Published: November 2017

AbstractWith the advent of high-throughput sequencing (HTS), profiling immunoglobulin (IG) repertoires has become an essential part of immunological research. Advances in sequencing technology enable the IonTorrent Personal Genome Machine (PGM) to cover the full-length of IG mRNA transcripts. Nucleotide insertions and deletions (indels) are the dominant errors of the PGM sequencing platform and can critically influence IG repertoire assessments. Here, we present a PGM-tailored IG repertoire sequencing approach combining error correction through unique molecular identifier (UID) barcoding and indel detection through ImMunoGeneTics (IMGT), the most commonly used sequence alignment database for IG sequences. Using artificially falsified sequences for benchmarking, we found that IMGT efficiently detects 98% of the introduced indels through gene-segment frameshifts. Undetected indels are either located at the ends of the sequences or produce masked frameshifts with an insertion and deletion in close proximity. IMGT’s indel correction algorithm resolves up to 87% of the tested insertions, but no deletions. The complementary determining regions 3 (CDR3s) are returned 100% correct for up to 3 insertions or 3 deletions through conservative culling. We further show, that our PGM-tailored unique molecular identifiers results in highly accurate HTS datasets if combined with the presented data processing. In this regard, considering sequences with at least two copies from datasets with UID families of minimum 3 reads result in correct sequences with over 99% confidence. The protocol and sample processing strategies described in this study will help to establish benchtop-scale sequencing of IG heavy chain transcripts in the field of IG repertoire research.
Quantifying Immune-Based Counterselection of Somatic Mutations
Authors: Yang Fan , Kim Dae-Kyum , Nakagawa Hidewaki , Hayashi Shuto , Imoto Seiya , Stein Lincoln , Roth Frederick P. 
Published: November 2017

ABSTRACTIt is now well established that somatic mutations in protein-coding regions can generate ‘neoantigens’, and that these can be recognized by the immune system and contribute to clearance of developing cancers. However, there is currently no model that can quantitatively predict the neoantigenic effect of any given somatic mutation. Here, we examined signatures of immune selection pressure on the distribution of somatic mutations. We quantified the extent to which somatic mutations are significantly depleted in peptides that are predicted to be displayed by major histocompatibility complex (MHC) class I proteins. We characterized the dependence of this depletion on expression level. We then examined whether immune selection pressure on somatic mutations changes depending on whether the patient had either one or two MHC-encoding alleles that can display the peptide. Our results indicate that MHC-encoding alleles are, in general, incompletely dominant, i.e., that having two copies of the display-enabling allele is more effective in displaying that peptide than having just one copy. More generally, a quantitative understanding of counter-selection of identifiable subclasses of neoantigenic somatic variation could guide immunotherapy or aid in developing personalized cancer vaccines.