1,721,034 research outputs found
Structure of the Lassa virus glycan shield provides a model for immunological resistance
No full textLassa virus is an Old World arenavirus endemic to West Africa that causes severe hemorrhagic fever. Vaccine development has focused on the envelope glycoprotein complex (GPC) that extends from the virion envelope. The often inadequate antibody immune response elicited by both vaccine and natural infection has been, in part, attributed to the abundance of N-linked glycosylation on the GPC. Here, using a virus-like−particle system that presents Lassa virus GPC in a native-like context, we determine the composite population of each of the N-linked glycosylation sites presented on the trimeric GPC spike. Our analysis reveals the presence of underprocessed oligomannose-type glycans, which form punctuated clusters that obscure the proteinous surface of both the GP1 attachment and GP2 fusion glycoprotein subunits of the Lassa virus GPC. These oligomannose clusters are seemingly derived as a result of sterically reduced accessibility to glycan processing enzymes, and limited amino acid diversification around these sites supports their role protecting against the humoral immune response. Combined, our data provide a structure-based blueprint for understanding how glycans render the glycoprotein spikes of Lassa virus and other Old World arenaviruses immunologically resistant targets
Revealing the evolutionary history and epidemiological dynamics of emerging RNA viral pathogens
Full text linkFast-evolving RNA viruses are a leading cause of morbidity and mortality among human
and animal populations, contributing significantly to both global health and economic
burden. The advent and revolution of high-throughput sequencing has empowered
phylogenetic analyses with increasing amounts of temporally and spatially sampled
viral data. Moreover, the parallel advancement in molecular evolution and phylogenetic
methods has provided investigators with a unique opportunity to gain detailed
insight into the evolutionary and epidemiological dynamics of emerging viral pathogens.
Using state-of-the-art statistical approaches, this thesis addresses some of the important
but controversial questions in viral emergence. Chapter 2 introduces a new
framework to quantify and investigate reassortment events in influenza A viruses. By
developing a computationally efficient algorithm to calculate the largest common subtree
for a pair of tree sets, which are estimated from diffe rent parts of the genome for
the same taxa set, the level of phylogenetic incongruency due to reassortment can be
appropriately ascertained. Chapters 3, 4 and 5 investigate the evolutionary origins of
three diff erent viruses: the novel emergence and cross-species transmission of SARSCoV,
the genesis and dissemination of the unique HCV circulating recombinant form,
and the ancient divergence of all influenza viruses, respectively. Moreover, Chapter 4
presents an improved statistical framework, which provides more precise evolutionary
estimates, by utilizing the hierarchical bayes approach to investigate recombination
events in emerging RNA viruses. The last empirical study, presented in Chapter 6, applies
the recently developed Bayesian phylogeography models to a large viral sequence
dataset sampled from southern Viet Nam to examine the fine-scale spatiotemporal dynamics
of endemic dengue in Southeast Asia.
The work presented here reflects both the advancements made in sequencing technology
and statistical phylogenetics, along with some of the challenges that remain in
studying the emergence of fast-evolving RNA viruses. This thesis proposes new and
improved solutions to these evolutionary problems, such as incorporating non-vertical
evolution (i.e. homologous recombination and reassortment) into the phylodynamic
framework, with the aim of facilitating future investigations of emerging viral diseases
High resolution evolutionary analysis of within-host hepatitis C virus infection
Full text linkBackground
Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population.
Method
We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics.
Results
We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10−7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection.
Conclusion
Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Vulnerabilities in coronavirus glycan shields despite extensive glycosylation
Full text linkSevere acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) coronaviruses (CoVs) are zoonotic pathogens with high fatality rates and pandemic potential. Vaccine development focuses on the principal target of the neutralizing humoral immune response, the spike (S) glycoprotein. Coronavirus S proteins are extensively glycosylated, encoding around 66-87 N-linked glycosylation sites per trimeric spike. Here, we reveal a specific area of high glycan density on MERS S that results in the formation of oligomannose-type glycan clusters, which were absent on SARS and HKU1 CoVs. We provide a comparison of the global glycan density of coronavirus spikes with other viral proteins including HIV-1 envelope, Lassa virus glycoprotein complex, and influenza hemagglutinin, where glycosylation plays a known role in shielding immunogenic epitopes. Overall, our data reveal how organisation of glycosylation across class I viral fusion proteins influence not only individual glycan compositions but also the immunological pressure across the protein surface.</p
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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