11 research outputs found
Host genotype and time dependent antigen presentation of viral peptides: predictions from theory
The rate of progression of HIV infected individuals to AIDS is known to vary with the genotype of the host, and is linked to their allele of human leukocyte antigen (HLA) proteins, which present protein degradation products at the cell surface to circulating T-cells. HLA alleles are associated with Gag-specific T-cell responses that are protective against progression of the disease. While Pol is the most conserved HIV sequence, its association with immune control is not as strong. To gain a more thorough quantitative understanding of the factors that contribute to immunodominance, we have constructed a model of the recognition of HIV infection by the MHC class I pathway. Our model predicts surface presentation of HIV peptides over time, demonstrates the importance of viral protein kinetics, and provides evidence of the importance of Gag peptides in the long-term control of HIV infection. Furthermore, short-term dynamics are also predicted, with simulation of virion-derived peptides suggesting that efficient processing of Gag can lead to a 50% probability of presentation within 3 hours post-infection, as observed experimentally. In conjunction with epitope prediction algorithms, this modelling approach could be used to refine experimental targets for potential T-cell vaccines, both for HIV and other viruses
Expression of ventricular-type myosin light chain messenger RNA in spontaneously hypertensive rat atria.
Compensatory mutation partially restores fitness and delays reversion of escape mutation within the immunodominant HLA-B*5703-restrieted gag epitope in chronic human immunodeficiency virus type 1 infection (vol 81, pg 8346, 2007)
Antioxidant potency of cumin varieties—cumin, black cumin and bitter cumin—on antioxidant systems
Determining process of occasional flooding from channel hydrological characteristics of Chel Basin, North Bengal (India)
Host genotype and time dependent antigen presentation of viral peptides: predictions from theory
Genome-wide scan for commons SNPs affecting bovine leukemia virus infection level in dairy cattle
Abstract Background Bovine leukemia virus (BLV) infection is omnipresent in dairy herds causing direct economic losses due to trade restrictions and lymphosarcoma-related deaths. Milk production drops and increase in the culling rate are also relevant and usually neglected. The BLV provirus persists throughout a lifetime and an inter-individual variation is observed in the level of infection (LI) in vivo. High LI is strongly correlated with disease progression and BLV transmission among herd mates. In a context of high prevalence, classical control strategies are economically prohibitive. Alternatively, host genomics studies aiming to dissect loci associated with LI are potentially useful tools for genetic selection programs tending to abrogate the viral spreading. The LI was measured through the proviral load (PVL) set–point and white blood cells (WBC) counts. The goals of this work were to gain insight into the contribution of SNPs (bovine 50KSNP panel) on LI variability and to identify genomics regions underlying this trait. Results We quantified anti–p24 response and total leukocytes count in peripheral blood from 1800 cows and used these to select 800 individuals with extreme phenotypes in WBCs and PVL. Two case-control genomic association studies using linear mixed models (LMMs) considering population stratification were performed. The proportion of the variance captured by all QC-passed SNPs represented 0.63 (SE ± 0.14) of the phenotypic variance for PVL and 0.56 (SE ± 0.15) for WBCs. Overall, significant associations (Bonferroni’s corrected -log10p > 5.94) were shared for both phenotypes by 24 SNPs within the Bovine MHC. Founder haplotypes were used to measure the linkage disequilibrium (LD) extent (r2 = 0.22 ± 0.27 at inter-SNP distance of 25−50 kb). The SNPs and LD blocks indicated genes potentially associated with LI in infected cows: i.e. relevant immune response related genes (DQA1, DRB3, BOLA-A, LTA, LTB, TNF, IER3, GRP111, CRISP1), several genes involved in cell cytoskeletal reorganization (CD2AP, PKHD1, FLOT1, TUBB5) and modelling of the extracellular matrix (TRAM2, TNXB). Host transcription factors (TFs) were also highlighted (TFAP2D; ABT1, GCM1, PRRC2A). Conclusions Data obtained represent a step forward to understand the biology of BLV–bovine interaction, and provide genetic information potentially applicable to selective breeding programs