Evidence map›Paper›PMID 35658003›Full record

ArticlePLoS computational biology2022

From affinity selection to kinetic selection in Germinal Centre modelling.

Danial Lashgari, Elena Merino Tejero, Michael Meyer-Hermann, Mathieu A F Claireaux, Marit J van Gils, Huub C J Hoefsloot, Antoine H C van Kampen

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 29% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
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

7 authors at 4 institutions in 2 countries.

Danial LashgariBioinformatics Laboratory, Epidemiology and Data Science, Amsterdam Public Health research institute, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands.ORCID 0000-0002-8748-2414
Elena Merino TejeroBioinformatics Laboratory, Epidemiology and Data Science, Amsterdam Public Health research institute, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands.ORCID 0000-0001-6325-7784
Michael Meyer-HermannDepartment for Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Braunschweig, Germany.ORCID 0000-0002-4300-2474
Mathieu A F ClaireauxDepartment of Medical Microbiology and Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands.ORCID 0000-0003-1890-9493
Marit J van GilsDepartment of Medical Microbiology and Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands.ORCID 0000-0003-3422-8161
Huub C J HoefslootBiosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands.ORCID 0000-0001-9963-0413
Antoine H C van KampenBioinformatics Laboratory, Epidemiology and Data Science, Amsterdam Public Health research institute, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands.ORCID 0000-0003-1025-7232
Amsterdam Institute for Addiction Research · NLAmsterdam University Medical Centers · NLHelmholtz Centre for Infection Research · DEUniversity of Amsterdam · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Affinity maturation is an evolutionary process by which the affinity of antibodies (Abs) against specific antigens (Ags) increases through rounds of B-cell proliferation, somatic hypermutation, and positive selection in germinal centres (GC). The positive selection of B cells depends on affinity, but the underlying mechanisms of affinity discrimination and affinity-based selection are not well understood. It has been suggested that selection in GC depends on both rapid binding of B-cell receptors (BcRs) to Ags which is kinetically favourable and tight binding of BcRs to Ags, which is thermodynamically favourable; however, it has not been shown whether a selection bias for kinetic properties is present in the GC. To investigate the GC selection bias towards rapid and tight binding, we developed an agent-based model of GC and compared the evolution of founder B cells with initially identical low affinities but with different association/dissociation rates for Ag presented by follicular dendritic cells in three Ag collection mechanisms. We compared an Ag collection mechanism based on association/dissociation rates of B-cell interaction with presented Ag, which includes a probabilistic rupture of bonds between the B-cell and Ag (Scenario-1) with a reference scenario based on an affinity-based Ag collection mechanism (Scenario-0). Simulations showed that the mechanism of Ag collection affects the GC dynamics and the GC outputs concerning fast/slow (un)binding of B cells to FDC-presented Ags. In particular, clones with lower dissociation rates outcompete clones with higher association rates in Scenario-1, while remaining B cells from clones with higher association rates reach higher affinities. Accordingly, plasma cell and memory B cell populations were biased towards B-cell clones with lower dissociation rates. Without such probabilistic ruptures during the Ag extraction process (Scenario-2), the selective advantage for clones with very low dissociation rates diminished, and the affinity maturation level of all clones decreased to the reference level.

Indexed as

B-LymphocytesGerminal CenterAntibody AffinityAntigensLymphocyte ActivationReceptors, Antigen, B-CellAntigensReceptors, Antigen, B-Cell

Identifiers

PMID35658003
PMCPMC9200358
OpenAlexW4281760689

What Socratic holds

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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 Socratic graph.