Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

A theory for how the antigen presentation profile influences the timing of T-cell detection

View ORCID ProfileAlberto Carignano, View ORCID ProfileNeil Dalchau
doi: https://doi.org/10.1101/480301
Alberto Carignano
1Biological Computation Group, Microsoft Research, Cambridge, CB1 2FB, UK
2Department of Electrical Engineering, University of Washington, WA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alberto Carignano
Neil Dalchau
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Neil Dalchau
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

T-cells are activated when their receptor molecules recognize complexes of MHC proteins bound to peptides on the surface of neighbouring cells. Each T-cell expresses one variant of many possible receptor molecules, which are generated through a partially random process that culminates in approximately 107 possible T-cell receptors. As the peptide sequence bound to an MHC molecule is also highly variable, the optimal strategy of an antigen-presenting cell for displaying peptide-MHC complexes is not obvious. A natural compromise arises between aggressive peptide filtering, displaying a few peptides with high stability MHC binding in high abundance and regularity, and promiscuous peptide binding, which can result in more diverse peptides being presented, but in lower abundance. To study this compromise, we have combined a model of MHC class I peptide filtering with a simple probabilistic description of the interactions between antigen presenting cells (APCs) and cytotoxic Tcells (CTLs). By asking how long it takes, on average, for an APC to encounter a circulating CTL that recognises one of the peptides being presented by its MHC molecules, we found that there often exists an optimal degree of peptide filtering, which minimises this expected time until first encounter. The optimal degree of filtering is often in the range of values that the chaperone molecule tapasin confers on peptide selection, but varies between MHC class I molecules that have different peptide binding properties. Our model-based analysis therefore helps to understand how variations in the antigen presentation profile might be exploited for vaccine design or immunotherapies.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted November 29, 2018.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
A theory for how the antigen presentation profile influences the timing of T-cell detection
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
A theory for how the antigen presentation profile influences the timing of T-cell detection
Alberto Carignano, Neil Dalchau
bioRxiv 480301; doi: https://doi.org/10.1101/480301
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
A theory for how the antigen presentation profile influences the timing of T-cell detection
Alberto Carignano, Neil Dalchau
bioRxiv 480301; doi: https://doi.org/10.1101/480301

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Immunology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4078)
  • Biochemistry (8750)
  • Bioengineering (6467)
  • Bioinformatics (23314)
  • Biophysics (11719)
  • Cancer Biology (9133)
  • Cell Biology (13227)
  • Clinical Trials (138)
  • Developmental Biology (7403)
  • Ecology (11360)
  • Epidemiology (2066)
  • Evolutionary Biology (15077)
  • Genetics (10390)
  • Genomics (14000)
  • Immunology (9109)
  • Microbiology (22025)
  • Molecular Biology (8772)
  • Neuroscience (47312)
  • Paleontology (350)
  • Pathology (1418)
  • Pharmacology and Toxicology (2480)
  • Physiology (3701)
  • Plant Biology (8043)
  • Scientific Communication and Education (1427)
  • Synthetic Biology (2206)
  • Systems Biology (6009)
  • Zoology (1247)