Allele-Specific Thresholds of Eluted Ligands for T-Cell Epitope Prediction.

A common strategy for predicting candidate human leukocyte antigen class I T-cell epitopes is to use an affinity-based threshold of 500 nM. Although a 500 nM threshold across alleles effectively identifies most epitopes across alleles, findings showing that major histocompatibility complex repertoire sizes vary by allele indicate that using thresholds specific to individual alleles may improve epitope identification. In this work, we compare different strategies utilizing common and allele-specific thresholds to identify an optimal approach for T-cell epitope prediction. First, we confirmed previous observations that different human leukocyte antigen class I alleles correspond with varying repertoire sizes. Here, we define general and allele-specific thresholds that capture 80% of eluted ligands and a different set of thresholds associated with capturing 9-mer T-cell epitopes at 80% sensitivity. Our analysis revealed that allele-specific threshold performance was roughly equivalent to that of a common threshold when considering a relatively large number of alleles. However, when predicting epitopes for only a few alleles, the use of allele-specific thresholds would be preferable. Finally, we present here for public use a set of allele-specific thresholds that may be used to identify T-cell epitopes at 80% sensitivity.

A behind-the-scenes tour of the IEDB curation process: an optimized process empirically integrating automation and human curation efforts.

The Immune Epitope Database and Analysis Resource (IEDB) provides the scientific community with open access to epitope data, as well as epitope prediction and analysis tools. The IEDB houses the most extensive collection of experimentally validated B-cell and T-cell epitope data, sourced primarily from published literature by expert curation. The data procurement requires systematic identification, categorization, curation and quality-checking processes. Here, we provide insights into these processes, with particular focus on the dividends they have paid in terms of attaining project milestones, as well as how objective analyses of our processes have identified opportunities for process optimization. These experiences are shared as a case study of the benefits of process implementation and review in biomedical big data, as well as to encourage idea-sharing among players in this ever-growing space.

Influenza Research Database: An integrated bioinformatics resource for influenza virus research.

The Influenza Research Database (IRD) is a U.S. National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Bioinformatics Resource Center dedicated to providing bioinformatics support for influenza virus research. IRD facilitates the research and development of vaccines, diagnostics and therapeutics against influenza virus by providing a comprehensive collection of influenza-related data integrated from various sources, a growing suite of analysis and visualization tools for data mining and hypothesis generation, personal workbench spaces for data storage and sharing, and active user community support. Here, we describe the recent improvements in IRD including the use of cloud and high performance computing resources, analysis and visualization of user-provided sequence data with associated metadata, predictions of novel variant proteins, annotations of phenotype-associated sequence markers and their predicted phenotypic effects, hemagglutinin (HA) clade classifications, an automated tool for HA subtype numbering conversion, linkouts to disease event data and the addition of host factor and antiviral drug components. All data and tools are freely available without restriction from the IRD website at https://www.fludb.org.

Dose-responsive gene expression in suberoylanilide hydroxamic acid-treated resting CD4+ T cells.

DESIGN: Persistent latently infected CD4 T cells represent a major obstacle to HIV eradication. Histone deacetylase inhibitors (HDACis) are a proposed activation therapy. However, off-target effects on gene expression in host immune cells are poorly understood. We hypothesized that HDACi-modulated genes would be best identified with a dose-response analysis. METHODS: Resting primary CD4 T cells were treated with 0.34, 1, 3, or 10 µmol/l of the HDACi, suberoylanilide hydroxamic acid (SAHA), for 24 h and subjected to microarray gene expression analysis. Genes with dose-correlated expression were filtered to identify a subset with consistent up or downregulation at each SAHA dose. Histone modifications were characterized in six SAHA dose-responsive genes by chromatin immunoprecipitation (ChIP-RT-qPCR). RESULTS: A large number of genes were shown to be upregulated (N = 657) or downregulated (N = 725) by SAHA in a dose-responsive manner (FDR-corrected P-value ≤ 0.5, fold change ≥|2|). Several genes (e.g. CINNAL1, DPEP2, H1F0, IRGM, PHF15, and SELL) are potential in-vivo biomarkers of SAHA activity. SAHA dose-responsive genes included transcription factors, HIV restriction factors, histone methyltransferases, and host proteins that interact with HIV. Pathway analysis suggested net downregulation of T-cell activation with increasing SAHA dose. Histone acetylation was not correlated with host gene expression, but plausible alternative mechanisms for SAHA-modulated gene expression were identified. CONCLUSION: Numerous genes in CD4 T cells are modulated by SAHA in a dose-responsive manner, including genes that may negatively influence HIV activation from latency. Our study suggests that SAHA influences gene expression through a confluence of several mechanisms, including histone modification, and altered expression and activity of transcription factors.

Vitamin D-responsive SGPP2 variants associated with lung cell expression and lung function.

BACKGROUND: Vitamin D is associated with lung health in epidemiologic studies, but mechanisms mediating observed associations are poorly understood. This study explores mechanisms for an effect of vitamin D in lung through an in vivo gene expression study, an expression quantitative trait loci (eQTL) analysis in lung tissue, and a population-based cohort study of sequence variants. METHODS: Microarray analysis investigated the association of gene expression in small airway epithelial cells with serum 25(OH)D in adult non-smokers. Sequence variants in candidate genes identified by the microarray were investigated in a lung tissue eQTL database, and also in relation to cross-sectional pulmonary function in the Health, Aging, and Body Composition (Health ABC) study, stratified by race, with replication in the Framingham Heart Study (FHS). RESULTS: 13 candidate genes had significant differences in expression by serum 25(OH)D (nominal p < 0.05), and a genome-wide significant eQTL association was detected for SGPP2. In Health ABC, SGPP2 SNPs were associated with FEV1 in both European- and African-Americans, and the gene-level association was replicated in European-American FHS participants. SNPs in 5 additional candidate genes (DAPK1, FSTL1, KAL1, KCNS3, and RSAD2) were associated with FEV1 in Health ABC participants. CONCLUSIONS: SGPP2, a sphingosine-1-phosphate phosphatase, is a novel vitamin D-responsive gene associated with lung function. The identified associations will need to be followed up in further studies.

Engineering of stable bispecific antibodies targeting IL-17A and IL-23.

Bispecific antibodies (bsAbs) present an attractive opportunity to combine the additive and potentially synergistic effects exhibited by combinations of monoclonal antibodies (mAbs). Current challenges for engineering bsAbs include retention of the binding affinity of the parent mAb or antibody fragment, the ability to bind both targets simultaneously, and matching valency with biology. Other factors to consider include structural stability and expression of the recombinant molecule, both of which may have significant impact on its development as a therapeutic. Here, we incorporate selection of stable, potent single-chain variable fragments (scFvs) early in the engineering process to assemble bsAbs for therapeutic applications targeting the cytokines IL-17A/A and IL-23. Stable scFvs directed against human cytokines IL-23p19 and IL-17A/A were isolated from a human Fab phage display library via batch conversion of panning output from Fabs to scFvs. This strategy integrated a step for shuffling V regions during the conversion and permitted the rescue of scFv molecules in both the V(H)V(L) and the V(L)V(H) orientations. Stable scFvs were identified and assembled into several bispecific formats as fusions to the Fc domain of human IgG1. The engineered bsAbs are potent neutralizers of the biological activity of both cytokines (IC(50) < 1 nM), demonstrate the ability to bind both target ligands simultaneously and display stability and productivity advantageous for successful manufacture of a therapeutic molecule. Pharmacokinetic analysis of the bsAbs in mice revealed serum half-lives similar to human mAbs. Assembly of bispecific molecules using stable antibody fragments offers an alternative to reformatting mAbs and minimizes subsequent structure-related and manufacturing concerns.

Identification of the IL-17 receptor related molecule IL-17RC as the receptor for IL-17F.

The proinflammatory cytokines IL-17A and IL-17F have a high degree of sequence similarity and share many biological properties. Both have been implicated as factors contributing to the progression of inflammatory and autoimmune diseases. Moreover, reagents that neutralize IL-17A significantly ameliorate disease severity in several mouse models of human disease. IL-17A mediates its effects through interaction with its cognate receptor, the IL-17 receptor (IL-17RA). We report here that the IL-17RA-related molecule, IL-17RC is the receptor for IL-17F. Notably, both IL-17A and IL-17F bind to IL-17RC with high affinity, leading us to suggest that a soluble form of this molecule may serve as an effective therapeutic antagonist of IL-17A and IL-17F. We generated a soluble form of IL-17RC and demonstrate that it effectively blocks binding of both IL-17A and IL-17F, and that it inhibits signaling in response to these cytokines. Collectively, our work indicates that IL-17RC functions as a receptor for both IL-17A and IL-17F and that a soluble version of this protein should be an effective antagonist of IL-17A and IL-17F mediated inflammatory diseases.