Large-scale mapping of the Ebola NP and GP proteins reveals multiple immunoprevalent and conserved CD4 T-cell epitopes.
Ontology highlight
ABSTRACT:
SUBMITTER: Gallais Y
PROVIDER: S-EPMC7214855 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Filoviruses (viruses in the genus Ebolavirus and Marburgvirus in the family Filoviridae) cause severe haemorrhagic fever in humans and nonhuman primates. Rapid, highly sensitive, and reliable filovirus-specific assays are required for diagnostics and outbreak control. Characterisation of antigenic sites in viral proteins can aid in the development of viral antigen detection assays such immunochromatography-based rapid diagnosis. We generated a panel of mouse monoclonal antibodies (mAbs) to the nucleoprotein (NP) of Ebola virus belonging to the species Zaire ebolavirus. The mAbs were divided into seven groups based on the profiles of their specificity and cross-reactivity to other species in the Ebolavirus genus. Using synthetic peptides corresponding to the Ebola virus NP sequence, the mAb binding sites were mapped to seven antigenic regions in the C-terminal half of the NP, including two highly conserved regions among all five Ebolavirus species currently known. Furthermore, we successfully produced species-specific rabbit antisera to synthetic peptides predicted to represent unique filovirus B-cell epitopes. Our data provide useful information for the development of Ebola virus antigen detection assays.
| S-EPMC3787873 | biostudies-literature
Project description:BackgroundLinkage Disequilibrium (LD) is a powerful approach for the identification and characterization of morphological shape, which usually involves multiple genetic markers. However, multiple testing corrections substantially reduce the power of the associated tests. In addition, the principle component analysis (PCA), used to quantify the shape variations into several principal phenotypes, further increases the number of tests. As a result, a powerful multiple testing correction for simultaneous large-scale gene-shape association tests is an essential part of determining statistical significance. Bonferroni adjustments and permutation tests are the most popular approaches to correcting for multiple tests within LD based Quantitative Trait Loci (QTL) models. However, permutations are extremely computationally expensive and may mislead in the presence of family structure. The Bonferroni correction, though simple and fast, is conservative and has low power for large-scale testing.ResultsWe propose a new multiple testing approach, constructed by combining an Intersection Union Test (IUT) with the Holm correction, which strongly controls the family-wise error rate (FWER) without any additional assumptions on the joint distribution of the test statistics or dependence structure of the markers. The power improvement for the Holm correction, as compared to the standard Bonferroni correction, is examined through a simulation study. A consistent and moderate increase in power is found under the majority of simulated circumstances, including various sample sizes, Heritabilities, and numbers of markers. The power gains are further demonstrated on real leaf shape data from a natural population of poplar, Populus szechuanica var tietica, where more significant QTL associated with morphological shape are detected than under the previously applied Bonferroni adjustment.ConclusionThe Holm correction is a valid and powerful method for assessing gene-shape association involving multiple markers, which not only controls the FWER in the strong sense but also improves statistical power.
| S-EPMC4118635 | biostudies-literature
Project description:Ebola is a Filovirus (FV) that induces a highly communicable and deadly hemorrhagic fever. Currently, there are no approved vaccines to treat FV infections. Protection from FV infection requires cell mediated and humoral immunity. Glycoprotein GP(1,2) Fc Zaire, a recombinant FV human Fc fusion protein, has been shown to confer protection against mouse adapted Zaire Ebola virus. The present studies are focused upon identifying immunodominant epitopes using in silico methods and developing tetramers as a diagnostic reagent to detect cell mediated immune responses to GP(1,2) Fc.The GP(1,2) Ebola Zaire sequence from the 1976 outbreak was analyzed by both BIMAS and SYFPEITHI algorithms to identify potential immuno-dominant epitopes. Several peptides were synthesized and screened in flow-based MHC stability studies. Three candidate peptides, P8, P9 and P10, were identified and, following immunization in Balb/c mice, all three peptides induced IFN-? as detected by ELISpot and intracellular staining.Significantly, P8, P9 and P10 generated robust cytotoxic T-cell responses (CTL) as determined by a flow cytometry-based Caspase assay. Antigen specific cells were also detected, using tetramers. Both P9 and P10 have sequence homology with highly conserved regions of several strains of FV.In sum, three immunodominant sequences of the Ebola GP(1,2) have been identified using in silico methods that may confer protection against mouse adapted Ebola Zaire. The development of tetramer reagents will provide unique insight into the potency and durability of medical countermeasure vaccines for known bioterrorism threat agents in preclinical models.
| S-EPMC4596288 | biostudies-literature
Project description:Distinguishing cell states based only on gene expression data remains a challenging task. This is true even for analyses within a species. In cross-species comparisons, the results obtained by different groups have varied widely. Here, we integrate RNA-seq data from more than 40 cell and tissue types of four mammalian species to identify sets of associated genes as indicators for specific cell states in each species. We employ a statistical method, TROM, to identify both protein-coding and non-coding indicators. Next, we map the cell states within each species and also between species using these indicator genes. We recapitulate known phenotypic similarity between related cell and tissue types and reveal molecular basis for their similarity. We also report novel associations between several tissues and cell types with functional support. Moreover, our identified conserved associated genes are found to be a good resource for studying cell differentiation and reprogramming. Lastly, long non-coding RNAs can serve well as associated genes to indicate cell states. We further infer the biological functions of those non-coding associated genes based on their co-expressed protein-coding genes. This study demonstrates that combining statistical modeling with public RNA-seq data can be powerful for improving our understanding of cell identity control.
| S-EPMC5389511 | biostudies-literature
Project description:Human rhinovirus (RV) is the most common cause of upper respiratory infections and exacerbations of asthma. In this work, we selected 14 peptides (6 from RV A and 8 from RV C) encompassing potential CD4 T cell epitopes. Peptides were selected for being highly conserved in RV A and C serotypes and predicted to bind to multiple human leukocyte antigen class II (HLA II) molecules. We found positive T cell recall responses by interferon gamma (IFNγ)-ELISPOT assays to eight peptides, validating seven of them (three from RV A and four from RV C) as CD4 T cell epitopes through intracellular cytokine staining assays. Additionally, we verified their promiscuous binding to multiple HLA II molecules by quantitative binding assays. According to their experimental HLA II binding profile, the combination of all these seven epitopes could be recognized by >95% of the world population. We actually determined IFNγ responses to a pool encompassing these CD4 T cell epitopes by intracellular cytokine staining, finding positive responses in 29 out of 30 donors. The CD4 T cell epitopes identified in this study could be key to monitor RV infections and to develop peptide-based vaccines against most RV A and C serotypes.
| S-EPMC8471592 | biostudies-literature
Project description:Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the TERT and CLPTM1L genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.
| S-EPMC8336922 | biostudies-literature
Project description:Influenza A viral nucleoprotein (NP) plays a critical role in virus replication and host adaptation, however, the underlying molecular evolutionary dynamics of NP lineages are less well-understood. In this study, large-scale analyses of 5094 NP nucleotide sequences revealed eight distinct evolutionary lineages, including three host-specific lineages (human, classical swine and equine), two cross-host lineages (Eurasian avian-like swine and swine-origin human pandemic H1N1 2009) and three geographically isolated avian lineages (Eurasian, North American and Oceanian). The average nucleotide substitution rate of the NP lineages was estimated to be 2.4 × 10(-3) substitutions per site per year, with the highest value observed in pandemic H1N1 2009 (3.4 × 10(-3)) and the lowest in equine (0.9 × 10(-3)). The estimated time of most recent common ancestor (TMRCA) for each lineage demonstrated that the earliest human lineage was derived around 1906, and the latest pandemic H1N1 2009 lineage dated back to December 17, 2008. A marked time gap was found between the times when the viruses emerged and were first sampled, suggesting the crucial role for long-term surveillance of newly emerging viruses. The selection analyses showed that human lineage had six positive selection sites, whereas pandemic H1N1 2009, classical swine, Eurasian avian and Eurasian swine had only one or two sites. Protein structure analyses revealed several positive selection sites located in epitope regions or host adaptation regions, indicating strong adaptation to host immune system pressures in influenza viruses. Along with previous studies, this study provides new insights into the evolutionary dynamics of influenza A NP lineages. Further lineage analyses of other gene segments will allow better understanding of influenza A virus evolution and assist in the improvement of global influenza surveillance.
| S-EPMC3204331 | biostudies-literature
Project description:Recent high-throughput single-cell sequencing approaches have been transformative for understanding complex cell populations, but are unable to provide additional phenotypic information, such as protein levels of cell-surface markers. Using oligonucleotide-labeled antibodies, we integrate measurements of cellular proteins and transcriptomes into an efficient, sequencing-based readout of single cells. This method is compatible with existing single-cell sequencing approaches and will readily scale as the throughput of these methods increase.
2017-07-31 | GSE100866 | GEO
Project description:This article focuses on mapping the Sun's large-scale magnetic fields. In particular, the model considers how photospheric fields evolve in time. Our solar field mapping method uses Netlogo's cellular automata software via algorithms to carry out the movement of magnetic field on the Sun via agents. This model's entities consist of two breeds: blue and red agents. The former carry a fixed amount of radially outward magnetic flux: 10(23) Mx, and the latter, the identical amount of inward directed flux. The individual agents are distinguished, for clarity, by various shades of blue and red arrows whose orientation indicates the direction the agents are moving, relative to the near-steady bulk fluid motions. The fluid motions generally advect the field with the well known meridional circulation and differential rotation. Our model predominantly focuses on spatial and temporal variations from the bulk fluid motions owing to magnetic interactions. There are but a few effects that agents have on each other: i) while at the poles, field agents are connected via the Babcock - Leighton (B - L) subsurface field to other latitudes. This allows them to undertake two duties there: A) the B - L subsurface field spawns the next generation of new magnetic field via new agents, and B) the B - L subsurface field attracts lower-latitude fields via the "long-range" magnetic stress tension; ii) nearby agents affect each other's motion by short-range interactions; and iii) through annihilation: when opposite field agents get too close to each other, they disappear in pairs. The behavior of the agents' long- and short-range magnetic forces is discussed within this paper as well as the model's use of internal boundary conditions. The workings of the model may be seen in the accompanying movies and/or by using the software available via SpringerPlus' website, or on the Netlogo (TM) community website, where help is readable available, and should all these fail, some help from the author.
| S-EPMC3601253 | biostudies-literature
Project description:Current HIV vaccine approaches are focused on immunogens encoding whole HIV antigenic proteins that mainly elicit cytotoxic CD8+ responses. Mounting evidence points toward a critical role for CD4+ T cells in the control of immunodeficiency virus replication, probably due to cognate help. Vaccine-induced CD4+ T cell responses might, therefore, have a protective effect in HIV replication. In addition, successful vaccines may have to elicit responses to multiple epitopes in a high proportion of vaccinees, to match the highly variable circulating strains of HIV. Using rational vaccine design, we developed a DNA vaccine encoding 18 algorithm-selected conserved, "promiscuous" (multiple HLA-DR-binding) B-subtype HIV CD4 epitopes - previously found to be frequently recognized by HIV-infected patients. We assessed the ability of the vaccine to induce broad T cell responses in the context of multiple HLA class II molecules using different strains of HLA class II- transgenic mice (-DR2, -DR4, -DQ6 and -DQ8). Mice displayed CD4+ and CD8+ T cell responses of significant breadth and magnitude, and 16 out of the 18 encoded epitopes were recognized. By virtue of inducing broad responses against conserved CD4+ T cell epitopes that can be recognized in the context of widely diverse, common HLA class II alleles, this vaccine concept may cope both with HIV genetic variability and increased population coverage. The vaccine may thus be a source of cognate help for HIV-specific CD8+ T cells elicited by conventional immunogens, in a wide proportion of vaccinees.
| S-EPMC2884037 | biostudies-literature