59 research outputs found

    Molecular Detection of Targeted Major Histocompatibility Complex I-Bound Peptides Using a Probabilistic Measure and Nanospray MS3 on a Hybrid Quadrupole-Linear Ion Trap

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    A nanospray MS3 method deployed on a quadrupole linear ion trap hybrid can detect targeted peptides with high dynamic range and high sensitivity from complex mixtures without separations. The method uses a recognition algorithm that is a modification of the relative (Kullback−Leibler, KL) entropy characterization of probabilistic distance to detect if reference MS3 fragmentation patterns are components of acquired MS3 spectra. The recognition reflects the probabilistic structure of physical MS measurements unlike the Euclidean or inner product metrics widely used for comparing spectra. It capably handles spectra with a significant chemical ion background in contrast to the Euclidean metric or the direct relative entropy. The full nanospray MS3 method allows both the detection and quantitation of targets without the need to obtain isotopically labeled standards. By avoiding chromatographic separations and its associated surface losses, the detection can be applied to complex samples on a very limited material scale. The methodology is illustrated by applications to the medically important problem of detecting targeted major histocompatibility complex (MHC) I associated peptides extracted from limited cell numbers

    PB1-F2 Finder: scanning influenza sequences for PB1-F2 encoding RNA segments

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    <p>Abstract</p> <p>Background</p> <p>PB1-F2 is a major virulence factor of influenza A. This protein is a product of an alternative reading frame in the PB1-encoding RNA segment 2. Its presence of is dictated by the presence or absence of premature stop codons. This virulence factor is present in every influenza pandemic and major epidemic of the 20th century. Absence of PB1-F2 is associated with mild disease, such as the 2009 H1N1 (“swine flu”).</p> <p>Results</p> <p>The analysis of 8608 segment 2 sequences showed that only 8.5% have been annotated for the presence of PB1-F2. Our analysis indicates that 75% of segment 2 sequences are likely to encode PB1-F2. Two major populations of PB1-F2 are of lengths 90 and 57 while minor populations include lengths 52, 63, 79, 81, 87, and 101. Additional possible populations include the lengths of 59, 69, 81, 95, and 106. Previously described sequences include only lengths 57, 87, and 90. We observed substantial variation in PB1-F2 sequences where certain variants show up to 35% difference to well-defined reference sequences. Therefore this dataset indicates that there are many more variants that need to be functionally characterized.</p> <p>Conclusions</p> <p>Our web-accessible tool PB1-F2 Finder enables scanning of influenza sequences for potential PB1-F2 protein products. It provides an initial screen and annotation of PB1-F2 products. It is accessible at <url>http://cvc.dfci.harvard.edu/pb1-f2</url>.</p

    Bioinformatic identification and characterization of human endothelial cell-restricted genes

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    <p>Abstract</p> <p>Background</p> <p>In this study, we used a systematic bioinformatics analysis approach to elucidate genes that exhibit an endothelial cell (EC) restricted expression pattern, and began to define their regulation, tissue distribution, and potential biological role.</p> <p>Results</p> <p>Using a high throughput microarray platform, a primary set of 1,191 transcripts that are enriched in different primary ECs compared to non-ECs was identified (LCB >3, FDR <2%). Further refinement of this initial subset of transcripts, using published data, yielded 152 transcripts (representing 109 genes) with different degrees of EC-specificity. Several interesting patterns emerged among these genes: some were expressed in all ECs and several were restricted to microvascular ECs. Pathway analysis and gene ontology demonstrated that several of the identified genes are known to be involved in vasculature development, angiogenesis, and endothelial function (P < 0.01). These genes are enriched in cardiovascular diseases, hemorrhage and ischemia gene sets (P < 0.001). Most of the identified genes are ubiquitously expressed in many different tissues. Analysis of the proximal promoter revealed the enrichment of conserved binding sites for 26 different transcription factors and analysis of the untranslated regions suggests that a subset of the EC-restricted genes are targets of 15 microRNAs. While many of the identified genes are known for their regulatory role in ECs, we have also identified several novel EC-restricted genes, the function of which have yet to be fully defined.</p> <p>Conclusion</p> <p>The study provides an initial catalogue of EC-restricted genes most of which are ubiquitously expressed in different endothelial cells.</p

    Elicitation from virus-naive individuals of cytotoxic T lymphocytes directed against conserved HIV-1 epitopes

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    Cytotoxic T lymphocytes (CTL) protect against viruses including HIV-1. To avoid viral escape mutants that thwart immunity, we chose 25 CTL epitopes defined in the context of natural infection with functional and/or structural constraints that maintain sequence conservation. By combining HLA binding predictions with knowledge concerning HLA allele frequencies, a metric estimating population protection coverage (PPC) was computed and epitope pools assembled. Strikingly, only a minority of immunocompetent HIV-1 infected individuals responds to pools with PPC >95%. In contrast, virus-naive individuals uniformly expand IFNγ producing cells and mount anti-HIV-1 cytolytic activity. This disparity suggests a vaccine design paradigm shift from infected to normal subjects

    Direct Identification of an HPV-16 Tumor Antigen from Cervical Cancer Biopsy Specimens

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    Persistent infection with high-risk human papilloma viruses (HPV) is the worldwide cause of many cancers, including cervical, anal, vulval, vaginal, penile, and oropharyngeal. Since T cells naturally eliminate the majority of chronic HPV infections by recognizing epitopes displayed on virally altered epithelium, we exploited Poisson detection mass spectrometry (MS3) to identify those epitopes and inform future T cell-based vaccine design. Nine cervical cancer biopsies from HPV-16 positive HLA-A*02 patients were obtained, histopathology determined, and E7 oncogene PCR-amplified from tumor DNA and sequenced. Conservation of E7 oncogene coding segments was found in all tumors. MS3 analysis of HLA-A*02 immunoprecipitates detected E711–19 peptide (YMLDLQPET) in seven of the nine tumor biopsies. The remaining two samples were E711–19 negative and lacked the HLA-A*02 binding GILT thioreductase peptide despite possessing binding-competent HLA-A*02 alleles. Thus, the conserved E711–19 peptide is a dominant HLA-A*02 binding tumor antigen in HPV-16 transformed cervical squamous and adenocarcinomas. Findings that a minority of HLA-A*02:01 tumors lack expression of both E711–19 and a peptide from a thioreductase important in processing of cysteine-rich proteins like E7 underscore the value of physical detection, define a potential additional tumor escape mechanism and have implications for therapeutic cancer vaccine development

    TANTIGEN 2.0: a knowledge base of tumor T cell antigens and epitopes

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    We previously developed TANTIGEN, a comprehensive online database cataloging more than 1000 T cell epitopes and HLA ligands from 292 tumor antigens. In TANTIGEN 2.0, we significantly expanded coverage in both immune response targets (T cell epitopes and HLA ligands) and tumor antigens. It catalogs 4,296 antigen variants from 403 unique tumor antigens and more than 1500 T cell epitopes and HLA ligands. We also included neoantigens, a class of tumor antigens generated through mutations resulting in new amino acid sequences in tumor antigens. TANTIGEN 2.0 contains validated TCR sequences specific for cognate T cell epitopes and tumor antigen gene/mRNA/protein expression information in major human cancers extracted by Human Pathology Atlas. TANTIGEN 2.0 is a rich data resource for tumor antigens and their associated epitopes and neoepitopes. It hosts a set of tailored data analytics tools tightly integrated with the data to form meaningful analysis workflows. It is freely available at http://projects.met-hilab.org/tadb

    Conservation analysis of dengue virust-cell epitope-based vaccine candidates using peptide block entropy

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    Broad coverage of the pathogen population is particularly important when designing CD8+ T-cell epitope vaccines against viral pathogens. Traditional approaches are based on combinations of highly conserved T-cell epitopes. Peptide block entropy analysis is a novel approach for assembling sets of broadly covering antigens. Since T-cell epitopes are recognized as peptides rather than individual residues, this method is based on calculating the information content of blocks of peptides from a multiple sequence alignment of homologous proteins rather than using the information content of individual residues. The block entropy analysis provides broad coverage of variant antigens. We applied the block entropy analysis method to the proteomes of the four serotypes of dengue virus (DENV) and found 1,551 blocks of 9-mer peptides, which cover 99% of available sequences with five or fewer unique peptides. In contrast, the benchmark study by Khan et al. (2008) resulted in 165 conserved 9-mer peptides. Many of the conserved blocks are located consecutively in the proteins. Connecting these blocks resulted in 78 conserved regions. Of the 1551 blocks of 9-mer peptides 110 comprised predicted HLA binder sets. In total, 457 subunit peptides that encompass the diversity of all sequenced DENV strains of which 333 are T-cell epitope candidates

    Human Leukocyte Antigen Typing Using a Knowledge Base Coupled with a High-Throughput Oligonucleotide Probe Array Analysis

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    Human leukocyte antigens (HLA) are important biomarkers because multiple diseases, drug toxicity, and vaccine responses reveal strong HLA associations. Current clinical HLA typing is an elimination process requiring serial testing. We present an alternative in situ synthesized DNA-based microarray method that contains hundreds of thousands of probes representing a complete overlapping set covering 1,610 clinically relevant HLA class I alleles accompanied by computational tools for assigning HLA type to 4-digit resolution. Our proof-of-concept experiment included 21 blood samples, 18 cell lines, and multiple controls. The method is accurate, robust, and amenable to automation. Typing errors were restricted to homozygous samples or those with very closely related alleles from the same locus, but readily resolved by targeted DNA sequencing validation of flagged samples. High-throughput HLA typing technologies that are effective, yet inexpensive, can be used to analyze the world’s populations, benefiting both global public health and personalized health care
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