Literature DB >> 20450869

A general method for characterization of humoral immunity induced by a vaccine or infection.

Joseph Barten Legutki1, D Mitchell Magee, Phillip Stafford, Stephen Albert Johnston.   

Abstract

A universal system to diagnose disease, characterize infection or evaluate the response to a vaccine would be useful. Towards this end we introduce a machine-readable platform that we term "Immunosignaturing". Rather than attempt to identify antibodies one by one, we splay the entire immune response across an array of 10,000 random sequence peptides. This segregates serum antibodies sufficiently to group and characterize responses caused by disease or vaccination. In the present study, we explore in detail the murine immunosignature to influenza A/PR/8/34 immunization and subsequent challenge. Even though the peptides are random sequence, the response to immunization and challenge is quite apparent. We find that the immunosignatures contained information not evident in whole virus ELISA. Antibody recognition of 283 influenza-specific peptides increased upon immunization and remained elevated for 211 days post-challenge. A set of 65 peptides, which overlapped 39 of the peptides that were consistent across time, was capable of distinguishing mice based on infectious dose, while whole virus ELISA could not. These peptide populations are consistently recognized in independent biological replicates of infection and are largely, but not solely, composed of virus reactive antibodies. The immunosignaturing analysis was expanded to analysis of human recipients of the 2006/2007 seasonal influenza vaccine. We find that 30 peptides are significantly recognized by all donors 21 days post-immunization and have the power to distinguish immune from pre-immune samples. Taken together the data suggest that immunosignaturing on a random peptide array can serve as a universal platform to assess antibody status in ways that cannot be replicated by conventional immunological assays. 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20450869     DOI: 10.1016/j.vaccine.2010.04.061

Source DB:  PubMed          Journal:  Vaccine        ISSN: 0264-410X            Impact factor:   3.641


  33 in total

1.  Evaluation of biological sample preparation for immunosignature-based diagnostics.

Authors:  Brian Andrew Chase; Stephen Albert Johnston; Joseph Barten Legutki
Journal:  Clin Vaccine Immunol       Date:  2012-01-11

2.  Exploring antibody recognition of sequence space through random-sequence peptide microarrays.

Authors:  Rebecca F Halperin; Phillip Stafford; Stephen Albert Johnston
Journal:  Mol Cell Proteomics       Date:  2010-11-09       Impact factor: 5.911

3.  General Assessment of Humoral Activity in Healthy Humans.

Authors:  Phillip Stafford; Daniel Wrapp; Stephen Albert Johnston
Journal:  Mol Cell Proteomics       Date:  2016-02-22       Impact factor: 5.911

4.  Epitope identification from fixed-complexity random-sequence peptide microarrays.

Authors:  Josh Richer; Stephen Albert Johnston; Phillip Stafford
Journal:  Mol Cell Proteomics       Date:  2014-11-03       Impact factor: 5.911

5.  Application of immunosignatures for diagnosis of valley fever.

Authors:  Krupa Arun Navalkar; Stephen Albert Johnston; Neal Woodbury; John N Galgiani; D Mitchell Magee; Zbigniew Chicacz; Phillip Stafford
Journal:  Clin Vaccine Immunol       Date:  2014-06-25

Review 6.  New approaches to understanding the immune response to vaccination and infection.

Authors:  David Furman; Mark M Davis
Journal:  Vaccine       Date:  2015-07-29       Impact factor: 3.641

7.  Immunosignatures can predict vaccine efficacy.

Authors:  Joseph Barten Legutki; Stephen Albert Johnston
Journal:  Proc Natl Acad Sci U S A       Date:  2013-10-28       Impact factor: 11.205

8.  Comparative study of classification algorithms for immunosignaturing data.

Authors:  Muskan Kukreja; Stephen Albert Johnston; Phillip Stafford
Journal:  BMC Bioinformatics       Date:  2012-06-21       Impact factor: 3.169

9.  A technology for developing synbodies with antibacterial activity.

Authors:  Valeriy Domenyuk; Andrey Loskutov; Stephen Albert Johnston; Chris W Diehnelt
Journal:  PLoS One       Date:  2013-01-23       Impact factor: 3.240

10.  Characterization of influenza vaccine immunogenicity using influenza antigen microarrays.

Authors:  Jordan V Price; Justin A Jarrell; David Furman; Nicole H Kattah; Evan Newell; Cornelia L Dekker; Mark M Davis; Paul J Utz
Journal:  PLoS One       Date:  2013-05-29       Impact factor: 3.240

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