145 research outputs found

    HLA-driven optimization of an HIV vaccine immunogen

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    Background: HIV diversity has been driven in large part by the intense selective pressure of HLA-restricted immune responses and is a significant challenge in HIV vaccine design. Sites of HLA-associated polymorphisms indicate potential immunogenic peptides that should be incorporated into an HIV vaccine. Method: Full-length (pretreatment) HIV sequencing and high-resolution HLA-A, -B, and -C genotyping was undertaken on 245 individuals in the Western Australian HIV Cohort Study. We determined statistically significant associations between polymorphisms in HIV sequences and HLA genotypes. Given these HLA associations we consider alternative measures of protection on the basis of the match between a viral peptide sequence and a corresponding segment of the vaccine. The measure is defined for all overlapping HIV peptides in the dataset. Each peptide contains a putative epitope and its associated flanking region. The vaccine is said to protect against a peptide sequence if the sites of HLA association in both the peptide sequence and the corresponding segment of the vaccine have nonescaped amino acids, and one of the following three criteria hold: (1), "no play"— the remaining sites in the peptide sequence and corresponding segment of the vaccine match exactly, (2), "mid-play"— the remaining sites in the sequence and vaccine differ only by conservative amino-acid substitutions, and (3) "full-play"—the remaining sites in the sequence and vaccine need have no relationship.The three criteria represent different assumptions about the degree to which T cells cross-react. An optimal vaccine immunogen of a given length is the one that contains the largest number of (possibly overlapping) protected against peptides. We provide a general machine-learning approach to optimization of such immunogens. Results: We optimized vaccines of length up to 2000 aa. The predicted efficacy of the optimized vaccine immunogens depends considerably on which criterion is used. For instance, an optimized vaccine immunogen of length 1300aa can protect against all peptides in the data under the full-play assumption, compared with 80% of all peptides under the mid-play assumption and 65% under the no-play assumption. Conclusion: These data demonstrate a novel, rational approach to optimizing the immunogenicity of an HIV vaccine against diverse circulating viruses in a human population, guided by knowledge of the population HLA

    POPULATION SEQUENCING FROM CHROMATOGRAM DATA *

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    One of the key components of sequencing technologies is proper separation of a single species/strain/allele of the targeted sequence from a sample. In traditional techniques, this has been achieved chemically (e.g., using specific primer sequences), however, multiple different but related species can still possibly be picked up with the same primer. This is especially problematic in sequencing RNA or proviral DNA, when the virus in question is highly variable and each individual is infected with a different swarm of viral strains. In case of HIV, for example, when the dominant sequences in the population differ by one or more insertions and deletions, the standard sequencing techniques fail to recover any of the components strains sufficiently well. We show that the chromatograms of mixed sequences can be used to accurately infer the individual strains, removing the need for additional sequencing steps, e.g. new primer synthesis or cloning of individual viral variants. To this purpose, we have developed a statistical generative model of raw chromatogram data and an appropriate inference algorithm based on maximizing the likelihood of an observed chromatogram. To illustrate this technique, we used an automated ABI 3730XL sequencer to capture mixed samples of pro-viral DNA of HIV-infected patients. The chromatograms of the mixed samples were analyzed by the presented algorithm, providing the inferred individual strains for each mixture as output. The mixture components were then compared with the sequences of the original clones. In many cases, the separated components had fewer than 1% differences to the ground truth which compares favorably to the output of the basic sequencer, whose errors went up to 40%

    Stel component analysis: Modeling spatial correlations in image class structure

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    A comparison of algorithms for inference and learning in probabilistic graphical models

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    Ustekinumab as Induction and Maintenance Therapy for Crohn’s Disease

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    BACKGROUND Ustekinumab, a monoclonal antibody to the p40 subunit of interleukin-12 and inter-leukin-23, was evaluated as an intravenous induction therapy in two populations with moderately to severely active Crohn’s disease. Ustekinumab was also evaluated as subcutaneous maintenance therapy. METHODS We randomly assigned patients to receive a single intravenous dose of ustekinumab (either 130 mg or approximately 6 mg per kilogram of body weight) or placebo in two induction trials. The UNITI-1 trial included 741 patients who met the criteria for primary or secondary nonresponse to tumor necrosis factor (TNF) antagonists or had unacceptable side effects. The UNITI-2 trial included 628 patients in whom conventional therapy failed or unacceptable side effects occurred. Patients who completed these induction trials then participated in IM-UNITI, in which the 397 patients who had a response to ustekinumab were randomly assigned to receive subcutaneous maintenance injections of 90 mg of ustekinumab (either every 8 weeks or every 12 weeks) or placebo. The primary end point for the induction trials was a clinical response at week 6 (defined as a decrease from baseline in the Crohn’s Disease Activity Index [CDAI] score of ≥100 points or a CDAI score <150). The primary end point for the maintenance trial was remission at week 44 (CDAI score <150). RESULTS The rates of response at week 6 among patients receiving intravenous ustekinumab at a dose of either 130 mg or approximately 6 mg per kilogram were significantly higher than the rates among patients receiving placebo (in UNITI-1, 34.3%, 33.7%, and 21.5%, respectively, with P≤0.003 for both comparisons with placebo; in UNITI-2, 51.7%, 55.5%, and 28.7%, respectively, with P<0.001 for both doses). In the groups receiving maintenance doses of ustekinumab every 8 weeks or every 12 weeks, 53.1% and 48.8%, respectively, were in remission at week 44, as compared with 35.9% of those receiving placebo (P = 0.005 and P = 0.04, respectively). Within each trial, adverse-event rates were similar among treatment groups. CONCLUSIONS Among patients with moderately to severely active Crohn’s disease, those receiving intravenous ustekinumab had a significantly higher rate of response than did those receiving placebo. Subcutaneous ustekinumab maintained remission in patients who had a clinical response to induction therapy. (Funded by Janssen Research and Development; ClinicalTrials.gov numbers, NCT01369329, NCT01369342, and NCT01369355.

    Gene Expression during the Generation and Activation of Mouse Neutrophils: Implication of Novel Functional and Regulatory Pathways

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    As part of the Immunological Genome Project (ImmGen), gene expression was determined in unstimulated (circulating) mouse neutrophils and three populations of neutrophils activated in vivo, with comparison among these populations and to other leukocytes. Activation conditions included serum-transfer arthritis (mediated by immune complexes), thioglycollate-induced peritonitis, and uric acid-induced peritonitis. Neutrophils expressed fewer genes than any other leukocyte population studied in ImmGen, and down-regulation of genes related to translation was particularly striking. However, genes with expression relatively specific to neutrophils were also identified, particularly three genes of unknown function: Stfa2l1, Mrgpr2a and Mrgpr2b. Comparison of genes up-regulated in activated neutrophils led to several novel findings: increased expression of genes related to synthesis and use of glutathione and of genes related to uptake and metabolism of modified lipoproteins, particularly in neutrophils elicited by thioglycollate; increased expression of genes for transcription factors in the Nr4a family, only in neutrophils elicited by serum-transfer arthritis; and increased expression of genes important in synthesis of prostaglandins and response to leukotrienes, particularly in neutrophils elicited by uric acid. Up-regulation of genes related to apoptosis, response to microbial products, NFkB family members and their regulators, and MHC class II expression was also seen, in agreement with previous studies. A regulatory model developed from the ImmGen data was used to infer regulatory genes involved in the changes in gene expression during neutrophil activation. Among 64, mostly novel, regulatory genes predicted to influence these changes in gene expression, Irf5 was shown to be important for optimal secretion of IL-10, IP-10, MIP-1α, MIP-1β, and TNF-α by mouse neutrophils in vitro after stimulation through TLR9. This data-set and its analysis using the ImmGen regulatory model provide a basis for additional hypothesis-based research on the importance of changes in gene expression in neutrophils in different conditions

    ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data

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    <p>Abstract</p> <p>Background</p> <p>With next-generation sequencing technologies, experiments that were considered prohibitive only a few years ago are now possible. However, while these technologies have the ability to produce enormous volumes of data, the sequence reads are prone to error. This poses fundamental hurdles when genetic diversity is investigated.</p> <p>Results</p> <p>We developed ShoRAH, a computational method for quantifying genetic diversity in a mixed sample and for identifying the individual clones in the population, while accounting for sequencing errors. The software was run on simulated data and on real data obtained in wet lab experiments to assess its reliability.</p> <p>Conclusions</p> <p>ShoRAH is implemented in C++, Python, and Perl and has been tested under Linux and Mac OS X. Source code is available under the GNU General Public License at <url>http://www.cbg.ethz.ch/software/shorah</url>.</p

    HLA-A is a Predictor of Hepatitis B e Antigen Status in HIV-Positive African Adults

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    Outcomes of chronic infection with hepatitis B virus (HBV) are varied, with increased morbidity reported in the context of human immunodeficiency virus (HIV) coinfection. The factors driving different outcomes are not well understood, but there is increasing interest in an HLA class I effect. We therefore studied the influence of HLA class I on HBV in an African HIV-positive cohort. We demonstrated that virologic markers of HBV disease activity (hepatitis B e antigen status or HBV DNA level) are associated with HLA-A genotype. This finding supports the role of the CD8+ T-cell response in HBV control, and potentially informs future therapeutic T-cell vaccine strategies.Version of Recor
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