Spatial heterogeneity and peptide availability determine CTL killing efficiency in vivo

The rate at which a cytotoxic T lymphocyte (CTL) can survey for infected cells is a key ingredient of models of vertebrate immune responses to intracellular pathogens. Estimates have been obtained using in vivo cytotoxicity assays in which peptide-pulsed splenocytes are killed by CTL in the spleens of immunised mice. However the spleen is a heterogeneous environment and splenocytes comprise multiple cell types. Are some cell types intrinsically more susceptible to lysis than others? Quantitatively, what impacts are made by the spatial distribution of targets and effectors, and the level of peptide-MHC on the target cell surface? To address these questions we revisited the splenocyte killing assay, using CTL specific for an epitope of influenza virus. We found that at the cell population level T cell targets were killed more rapidly than B cells. Using modeling, quantitative imaging and in vitro killing assays we conclude that this difference in vivo likely reflects different migratory patterns of targets within the spleen and a heterogeneous distribution of CTL, with no detectable difference in the intrinsic susceptibilities of the two populations to lysis. Modeling of the stages involved in the detection and killing of peptide-pulsed targets in vitro revealed that peptide dose influenced the ability of CTL to form conjugates with targets but had no detectable effect on the probability that conjugation resulted in lysis, and that T cell targets took longer to lyse than B cells. We also infer that incomplete killing in vivo of cells pulsed with low doses of peptide may be due to a combination of heterogeneity in peptide uptake and the dissociation, but not internalisation, of peptide-MHC complexes. Our analyses demonstrate how population-averaged parameters in models of immune responses can be dissected to account for both spatial and cellular heterogeneity

Assessment of trabecular bone score, an index of bone microarchitecture, in HIV positive and HIV negative persons within the HIV UPBEAT cohort

Introduction Increased prevalence of low bone mineral density (BMD) and increased fracture incidence are observed in persons living with HIV (PLWH). The trabecular bone score (TBS) is a novel index of bone microarchitecture which improves fracture prediction independent of BMD. Methods The HIV UPBEAT study is a single centre, prospective cohort study that enrolled subjects with and without HIV from similar sociodemographic backgrounds for annual assessments of bone health. TBS was derived from lumbar spine (LS) dual-energy X-ray absorptiometry images. Univariate and multivariable linear regression was used to assess relationships between baseline TBS, BMD, sociodemographic and clinical factors. Results 463 subjects (201 HIV positive) were included; PLWH were younger and more likely male, of non-African ethnicity and current smokers. HIV was associated with a mean reduction of 0.037 [-0.060, -0.013] (p = 0.002) in TBS. Lower TBS was also associated with male gender, non-African ethnicity, current smoking status and lower LS BMD. HIV remained associated with lower TBS after adjustment for LS BMD, age, gender and ethnicity. However, adjustment for current smoking significantly attenuated the association between HIV and TBS, with further adjustment for higher bone turnover markers largely explaining any residual association. Among the sub-group of PLWH, exposure to protease inhibitors and lower nadir CD4+ T-cell counts were both predictors of lower TBS. Conclusions PLWH have lower TBS independent of LS BMD. However, this is largely explained by higher current smoking rates and higher bone turnover in those with HIV. Exposure to PI, but not tenofovir disproxil fumarate, also contributed to lower TBS in those with HIV

Changed epitopes drive the antigenic drift for influenza A (H3N2) viruses

<p>Abstract</p> <p>Background</p> <p>In circulating influenza viruses, gradually accumulated mutations on the glycoprotein hemagglutinin (HA), which interacts with infectivity-neutralizing antibodies, lead to the escape of immune system (called antigenic drift). The antibody recognition is highly correlated to the conformation change on the antigenic sites (epitopes), which locate on HA surface. To quantify a changed epitope for escaping from neutralizing antibodies is the basis for the antigenic drift and vaccine development.</p> <p>Results</p> <p>We have developed an epitope-based method to identify the antigenic drift of influenza A utilizing the conformation changes on epitopes. A changed epitope, an antigenic site on HA with an accumulated conformation change to escape from neutralizing antibody, can be considered as a "key feature" for representing the antigenic drift. According to hemagglutination inhibition (HI) assays and HA/antibody complex structures, we statistically measured the conformation change of an epitope by considering the number of critical position mutations with high genetic diversity and antigenic scores. Experimental results show that two critical position mutations can induce the conformation change of an epitope to escape from the antibody recognition. Among five epitopes of HA, epitopes A and B, which are near to the receptor binding site, play a key role for neutralizing antibodies. In addition, two changed epitopes often drive the antigenic drift and can explain the selections of 24 WHO vaccine strains.</p> <p>Conclusions</p> <p>Our method is able to quantify the changed epitopes on HA for predicting the antigenic variants and providing biological insights to the vaccine updates. We believe that our method is robust and useful for studying influenza virus evolution and vaccine development.</p

Revisiting Estimates of CTL Killing Rates In Vivo

Recent experimental advances have allowed the estimation of the in vivo rates of killing of infected target cells by cytotoxic T lymphocytes (CTL). We present several refinements to a method applied previously to quantify killing of targets in the spleen using a dynamical model. We reanalyse data previously used to estimate killing rates of CTL specific for two epitopes of lymphocytic choriomeningitis virus (LCMV) in mice and show that, contrary to previous estimates the “killing rate” of effector CTL is approximately twice that of memory CTL. Further, our method allows the fits to be visualized, and reveals one potentially interesting discrepancy between fits and data. We discuss extensions to the basic CTL killing model to explain this discrepancy and propose experimental tests to distinguish between them

The Genetics of Adaptation for Eight Microvirid Bacteriophages

Theories of adaptive molecular evolution have recently experienced significant expansion, and their predictions and assumptions have begun to be subjected to rigorous empirical testing. However, these theories focus largely on predicting the first event in adaptive evolution, the fixation of a single beneficial mutation. To address long-term adaptation it is necessary to include new assumptions, but empirical data are needed for guidance. To empirically characterize the general properties of adaptive walks, eight recently isolated relatives of the single-stranded DNA (ssDNA) bacteriophage φX174 (family Microviridae) were adapted to identical selective conditions. Three of the eight genotypes were adapted in replicate, for a total of 11 adaptive walks. We measured fitness improvement and identified the genetic changes underlying the observed adaptation. Nearly all phages were evolvable; nine of the 11 lineages showed a significant increase in fitness. However, fitness plateaued quickly, and adaptation was achieved through only three substitutions on average. Parallel evolution was rampant, both across replicates of the same genotype as well as across different genotypes, yet adaptation of replicates never proceeded through the exact same set of mutations. Despite this, final fitnesses did not vary significantly among replicates. Final fitnesses did vary significantly across genotypes but not across phylogenetic groupings of genotypes. A positive correlation was found between the number of substitutions in an adaptive walk and the magnitude of fitness improvement, but no correlation was found between starting and ending fitness. These results provide an empirical framework for future adaptation theory

Phylogenetic Diversity and Genotypical Complexity of H9N2 Influenza A Viruses Revealed by Genomic Sequence Analysis

H9N2 influenza A viruses have become established worldwide in terrestrial poultry and wild birds, and are occasionally transmitted to mammals including humans and pigs. To comprehensively elucidate the genetic and evolutionary characteristics of H9N2 influenza viruses, we performed a large-scale sequence analysis of 571 viral genomes from the NCBI Influenza Virus Resource Database, representing the spectrum of H9N2 influenza viruses isolated from 1966 to 2009. Our study provides a panoramic framework for better understanding the genesis and evolution of H9N2 influenza viruses, and for describing the history of H9N2 viruses circulating in diverse hosts. Panorama phylogenetic analysis of the eight viral gene segments revealed the complexity and diversity of H9N2 influenza viruses. The 571 H9N2 viral genomes were classified into 74 separate lineages, which had marked host and geographical differences in phylogeny. Panorama genotypical analysis also revealed that H9N2 viruses include at least 98 genotypes, which were further divided according to their HA lineages into seven series (A–G). Phylogenetic analysis of the internal genes showed that H9N2 viruses are closely related to H3, H4, H5, H7, H10, and H14 subtype influenza viruses. Our results indicate that H9N2 viruses have undergone extensive reassortments to generate multiple reassortants and genotypes, suggesting that the continued circulation of multiple genotypical H9N2 viruses throughout the world in diverse hosts has the potential to cause future influenza outbreaks in poultry and epidemics in humans. We propose a nomenclature system for identifying and unifying all lineages and genotypes of H9N2 influenza viruses in order to facilitate international communication on the evolution, ecology and epidemiology of H9N2 influenza viruses

Seasonality of Influenza A(H3N2) Virus: A Hong Kong Perspective (1997–2006)

BACKGROUND: The underlying basis for the seasonality of influenza A viruses is still uncertain. Phylogenetic studies investigated this phenomenon but have lacked sequences from more subtropical and tropical regions, particularly from Southeast Asia. METHODOLOGY/PRINCIPAL FINDINGS: 281 complete hemagglutinin (HA) and neuraminidase (NA) sequences were obtained from influenza A(H3N2) viruses, collected over 10 years (1997-2006) from Hong Kong. These dated sequences were analyzed with influenza A(H3N2) vaccine strain sequences (Syd/5/97, Mos/10/99, Fuj/411/02, Cal/7/04) and 315 other publicly available dated sequences from elsewhere, worldwide. In addition, the NA sequence alignment was inspected for the presence of any naturally occurring, known, neuraminidase inhibitor (NAI) resistance-associated amino acid mutations (R292K and E119V). Before 2001, the Hong Kong HA and NA sequences clustered more closely with the older vaccine sequences (Syd/5/97, Mos/10/99) than did sequences from elsewhere. After 2001, this trend reversed with significant clusters containing HA and NA sequences from different locations, isolated at different times, suggesting that viral migration may account for much of the influenza A(H3N2) seasonality during this 10-year period. However, at least one example from Hong Kong was found suggesting that in some years, influenza A(H3N2) viruses may persist in the same location, perhaps continuing to circulate, sub-clinically, at low levels between seasons, to re-emerge in the influenza season the following year, relatively unchanged. None of these Hong Kong influenza A(H3N2) NA sequences contained any of the known NAI-resistance associated mutations. CONCLUSIONS/SIGNIFICANCE: The seasonality of influenza A(H3N2) may be largely due to global migration, with similar viruses appearing in different countries at different times. However, occasionally, some viruses may remain within a single location and continue to circulate within that population, to re-emerge during the next influenza season, with relatively little genetic change. Naturally occurring NAI resistance mutations were absent or, at least, very rare in this population

Panorama Phylogenetic Diversity and Distribution of Type A Influenza Virus

Type A influenza virus is one of important pathogens of various animals, including humans, pigs, horses, marine mammals and birds. Currently, the viral type has been classified into 16 hemagglutinin and 9 neuraminidase subtypes, but the phylogenetic diversity and distribution within the viral type largely remain unclear from the whole view.The panorama phylogenetic trees of influenza A viruses were calculated with representative sequences selected from approximately 23000 candidates available in GenBank using web servers in NCBI and the software MEGA 4.0. Lineages and sublineages were classified according to genetic distances, topology of the phylogenetic trees and distributions of the viruses in hosts, regions and time.Here, two panorama phylogenetic trees of type A influenza virus covering all the 16 hemagglutinin subtypes and 9 neuraminidase subtypes, respectively, were generated. The trees provided us whole views and some novel information to recognize influenza A viruses including that some subtypes of avian influenza viruses are more complicated than Eurasian and North American lineages as we thought in the past. They also provide us a framework to generalize the history and explore the future of the viral circulation and evolution in different kinds of hosts. In addition, a simple and comprehensive nomenclature system for the dozens of lineages and sublineages identified within the viral type was proposed, which if universally accepted, will facilitate communications on the viral evolution, ecology and epidemiology

Nephele: genotyping via complete composition vectors and MapReduce

<p>Abstract</p> <p>Background</p> <p>Current sequencing technology makes it practical to sequence many samples of a given organism, raising new challenges for the processing and interpretation of large genomics data sets with associated metadata. Traditional computational phylogenetic methods are ideal for studying the evolution of gene/protein families and using those to infer the evolution of an organism, but are less than ideal for the study of the whole organism mainly due to the presence of insertions/deletions/rearrangements. These methods provide the researcher with the ability to group a set of samples into distinct genotypic groups based on sequence similarity, which can then be associated with metadata, such as host information, pathogenicity, and time or location of occurrence. Genotyping is critical to understanding, at a genomic level, the origin and spread of infectious diseases. Increasingly, genotyping is coming into use for disease surveillance activities, as well as for microbial forensics. The classic genotyping approach has been based on phylogenetic analysis, starting with a multiple sequence alignment. Genotypes are then established by expert examination of phylogenetic trees. However, these traditional single-processor methods are suboptimal for rapidly growing sequence datasets being generated by next-generation DNA sequencing machines, because they increase in computational complexity quickly with the number of sequences.</p> <p>Results</p> <p>Nephele is a suite of tools that uses the complete composition vector algorithm to represent each sequence in the dataset as a vector derived from its constituent k-mers by passing the need for multiple sequence alignment, and affinity propagation clustering to group the sequences into genotypes based on a distance measure over the vectors. Our methods produce results that correlate well with expert-defined clades or genotypes, at a fraction of the computational cost of traditional phylogenetic methods run on traditional hardware. Nephele can use the open-source Hadoop implementation of MapReduce to parallelize execution using multiple compute nodes. We were able to generate a neighbour-joined tree of over 10,000 16S samples in less than 2 hours.</p> <p>Conclusions</p> <p>We conclude that using Nephele can substantially decrease the processing time required for generating genotype trees of tens to hundreds of organisms at genome scale sequence coverage.</p