Abstract

Antibodies are critical components of adaptive immunity, binding with high affinity to pathogenic epitopes. Antibodies undergo rigorous selection to achieve this high affinity, yet some maintain an additional basal level of low affinity, broad reactivity to diverse epitopes, a phenomenon termed 'polyreactivity'. While polyreactivity has been observed in antibodies isolated from various immunological niches, the biophysical properties that allow for promiscuity in a protein selected for high affinity binding to a single target remain unclear. Using a database of over 1,000 polyreactive and non-polyreactive antibody sequences, we created a bioinformatic pipeline to isolate key determinants of polyreactivity. These determinants, which include an increase in inter-loop crosstalk and a propensity for a neutral binding surface, are sufficient to generate a classifier able to identify polyreactive antibodies with over 75% accuracy. The framework from which this classifier was built is generalizable, and represents a powerful, automated pipeline for future immune repertoire analysis.

Data availability

All data generated and all code used for analysis in this study has been published on GitHub at github.com/ctboughter/AIMS.

Article and author information

Author details

  1. Christopher T Boughter

    Graduate Program in Biophysical Sciences, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Marta T Borowska

    Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Jenna J Guthmiller

    Department of Medicine, Section of Rheumatology, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Albert Bendelac

    Department of Medicine, Section of Rheumatology, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Patrick C Wilson

    Department of Medicine, Section of Rheumatology, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Benoit Roux

    Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5254-2712
  7. Erin J Adams

    Department of Biochemistry and Molecular Biology; Committee on Immunology, University of Chicago, Chicago, United States
    For correspondence
    ejadams@uchicago.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6271-8574

Funding

National Institute of Biomedical Imaging and Bioengineering (EB009412)

  • Christopher T Boughter

National Institute of Allergy and Infectious Diseases (AI147954)

  • Christopher T Boughter
  • Marta T Borowska
  • Erin J Adams

National Institute of Allergy and Infectious Diseases (AI115471)

  • Christopher T Boughter
  • Marta T Borowska
  • Erin J Adams

National Science Foundation (MCB-1517221)

  • Christopher T Boughter
  • Benoit Roux

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Pamela J Bjorkman, California Institute of Technology, United States

Version history

  1. Received: July 23, 2020
  2. Accepted: November 9, 2020
  3. Accepted Manuscript published: November 10, 2020 (version 1)
  4. Version of Record published: December 22, 2020 (version 2)

Copyright

© 2020, Boughter et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Christopher T Boughter
  2. Marta T Borowska
  3. Jenna J Guthmiller
  4. Albert Bendelac
  5. Patrick C Wilson
  6. Benoit Roux
  7. Erin J Adams
(2020)
Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops
eLife 9:e61393.
https://doi.org/10.7554/eLife.61393

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https://doi.org/10.7554/eLife.61393

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    Prinflammatory extracellular chromatin from neutrophil extracellular traps (NETs) and other cellular sources is found in COVID-19 patients and may promote pathology. We determined whether pulmonary administration of the endonuclease dornase alfa reduced systemic inflammation by clearing extracellular chromatin.

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    Eligible patients were randomized (3:1) to the best available care including dexamethasone (R-BAC) or to BAC with twice-daily nebulized dornase alfa (R-BAC + DA) for seven days or until discharge. A 2:1 ratio of matched contemporary controls (CC-BAC) provided additional comparators. The primary endpoint was the improvement in C-reactive protein (CRP) over time, analyzed using a repeated-measures mixed model, adjusted for baseline factors.

    Results:

    We recruited 39 evaluable participants: 30 randomized to dornase alfa (R-BAC +DA), 9 randomized to BAC (R-BAC), and included 60 CC-BAC participants. Dornase alfa was well tolerated and reduced CRP by 33% compared to the combined BAC groups (T-BAC). Least squares (LS) mean post-dexamethasone CRP fell from 101.9 mg/L to 23.23 mg/L in R-BAC +DA participants versus a 99.5 mg/L to 34.82 mg/L reduction in the T-BAC group at 7 days; p=0.01. The anti-inflammatory effect of dornase alfa was further confirmed with subgroup and sensitivity analyses on randomised participants only, mitigating potential biases associated with the use of CC-BAC participants. Dornase alfa increased live discharge rates by 63% (HR 1.63, 95% CI 1.01–2.61, p=0.03), increased lymphocyte counts (LS mean: 1.08 vs 0.87, p=0.02) and reduced circulating cf-DNA and the coagulopathy marker D-dimer (LS mean: 570.78 vs 1656.96 μg/mL, p=0.004).

    Conclusions:

    Dornase alfa reduces pathogenic inflammation in COVID-19 pneumonia, demonstrating the benefit of cost-effective therapies that target extracellular chromatin.

    Funding:

    LifeArc, Breathing Matters, The Francis Crick Institute (CRUK, Medical Research Council, Wellcome Trust).

    Clinical trial number:

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