Evidence map›Paper›PMID 25104221›Full record

ArticleBMC bioinformatics2014

Integrated assessment of predicted MHC binding and cross-conservation with self reveals patterns of viral camouflage.

Lu He, Anne S De Groot, Andres H Gutierrez, William D Martin, Lenny Moise, Chris Bailey-Kellogg

Abstract read
In one paragraph

Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

  1. In Silico Design of a Chimeric Humanized L-asparaginase.International journal of molecular sciences · 2023
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  6. Frontiers in immunology · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lu He
Anne S De Groot
Andres H Gutierrez
William D Martin
Lenny Moise
Chris Bailey-Kellogg

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImmune recognition of foreign proteins by T cells hinges on the formation of a ternary complex sandwiching a constituent peptide of the protein between a major histocompatibility complex (MHC) molecule and a T cell receptor (TCR). Viruses have evolved means of "camouflaging" themselves, avoiding immune recognition by reducing the MHC and/or TCR binding of their constituent peptides. Computer-driven T cell epitope mapping tools have been used to evaluate the degree to which particular viruses have used this means of avoiding immune response, but most such analyses focus on MHC-facing 'agretopes'. Here we set out a new means of evaluating the TCR faces of viral peptides in addition to their agretopes, integrating evaluations of both sides of the ternary complex in a single analysis.

methodsThis paper develops what we call the Janus Immunogenicity Score (JIS), bringing together a well-established method for predicting MHC binding, with a novel assessment of the potential for TCR binding based on similarity with self. Intuitively, both good MHC binding and poor self-similarity are required for high immunogenicity (i.e., a robust T effector response).

resultsFocusing on the class II antigen-processing pathway, we show that the JIS of T effector epitopes and null or regulatory epitopes deposited in a large database of epitopes (Immune Epitope Database) are significantly different. We then show that different types of viruses display significantly different patterns of scores over their constituent peptides, with viruses causing chronic infection (Epstein-Barr and cytomegalovirus) strongly shifted to lower scores relative to those causing acute infection (Ebola and Marburg). Similarly we find distinct patterns among influenza proteins in H1N1 (a strain against which human populations rapidly developed immunity) and H5N1 and H7N9 (highly pathogenic avian flu strains, with significantly greater case mortality rates).

conclusionThe Janus Immunogenicity Score, which integrates MHC binding and TCR cross-reactivity, provides a new tool for studying immunogenicity of pathogens and may improve the selection and optimization of antigenic elements for vaccine design.

Indexed as

Major Histocompatibility ComplexAnimalsComputational BiologyCross ReactionsDatabases, FactualEpitopes, T-LymphocyteHistocompatibility Antigens Class IIHumansInfluenza A Virus, H1N1 SubtypeInfluenza A Virus, H5N1 SubtypeInfluenza, HumanModels, BiologicalModels, MolecularOrthomyxoviridae InfectionsReceptors, Antigen, T-CellT-LymphocytesEpitopes, T-LymphocyteHistocompatibility Antigens Class IIReceptors, Antigen, T-CellViral ProteinsViral Vaccines

Identifiers

PMID25104221
PMCPMC4094998

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.