Evidence map›Paper›PMID 32747563›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Optimizing immunization protocols to elicit broadly neutralizing antibodies.

Kayla G Sprenger, Joy E Louveau, Pranav M Murugan, Arup K Chakraborty

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
2.9field-weighted citation impact, top 8% of its field
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

35 citing papers in PubMed, 59 citations in OpenAlex.

  1. Article
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  4. Retrospective SARS-CoV-2 human antibody development trajectories are largely sparse and permissive.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Epistatic hotspots organize antibody fitness landscape and boost evolvability.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  6. Bioinformatics advances · 2025
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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

4 authors at 3 institutions in 1 country.

Kayla G SprengerInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139.
Joy E LouveauHarvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139.
Pranav M MuruganInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139.ORCID 0000-0003-2715-0781
Arup K ChakrabortyInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139; arupc@mit.edu.
Massachusetts Institute of Technology · USHarvard–MIT Division of Health Sciences and Technology · USRagon Institute of MGH, MIT and Harvard · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural infections and vaccination with a pathogen typically stimulate the production of potent antibodies specific for the pathogen through a Darwinian evolutionary process known as affinity maturation. Such antibodies provide protection against reinfection by the same strain of a pathogen. A highly mutable virus, like HIV or influenza, evades recognition by these strain-specific antibodies via the emergence of new mutant strains. A vaccine that elicits antibodies that can bind to many diverse strains of the virus-known as broadly neutralizing antibodies (bnAbs)-could protect against highly mutable pathogens. Despite much work, the mechanisms by which bnAbs emerge remain uncertain. Using a computational model of affinity maturation, we studied a wide variety of vaccination strategies. Our results suggest that an effective strategy to maximize bnAb evolution is through a sequential immunization protocol, wherein each new immunization optimally increases the pressure on the immune system to target conserved antigenic sites, thus conferring breadth. We describe the mechanisms underlying why sequentially driving the immune system increasingly further from steady state, in an optimal fashion, is effective. The optimal protocol allows many evolving B cells to become bnAbs via diverse evolutionary paths.

Indexed as

Immunization ScheduleVaccinationAntibodies, NeutralizingAntibody AffinityB-LymphocytesComputer SimulationHIV-1HumansInfluenza A virusModels, ChemicalModels, MolecularProtein BindingProtein ConformationThermodynamicsViral VaccinesAntibodies, NeutralizingViral Vaccinesbroadly neutralizing antibodiesevolutionary biologyhighly mutable pathogenssequential vaccinationstatistical mechanics

Identifiers

PMID32747563
PMCPMC7443869
OpenAlexW3047376062

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.