Evidence map›Paper›PMID 35759459›Full record

ArticlePLoS computational biology2022

Mathematical modeling of the microtubule detyrosination/tyrosination cycle for cell-based drug screening design.

Jeremy Grignard, Véronique Lamamy, Eva Vermersch, Philippe Delagrange, Jean-Philippe Stephan, Thierry Dorval, François Fages

Abstract 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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.

Jeremy GrignardPole of Activity Data Sciences and Data Management, Institut de Recherches Servier (IdRS), Croissy-sur-Seine, France.ORCID 0000-0002-9861-1744
Véronique LamamyPole of Activity Cellular Sciences, Institut de Recherches Servier (IdRS), Croissy-sur-Seine, France.ORCID 0000-0002-2042-8667
Eva VermerschPole of Activity Cellular Sciences, Institut de Recherches Servier (IdRS), Croissy-sur-Seine, France.ORCID 0000-0003-4813-2355
Philippe DelagrangeTherapeutic Area Neuropsychiatry and Immunoinflammation, Institut de Recherches Servier (IdRS), Croissy-sur-Seine, France.ORCID 0000-0002-7456-0081
Jean-Philippe StephanIn Vitro Pharmacology Unit, Institut de Recherches Servier (IdRS), Croissy-sur-Seine, France.
Thierry DorvalPole of Activity Data Sciences and Data Management, Institut de Recherches Servier (IdRS), Croissy-sur-Seine, France.
François FagesTeam Project Lifeware, Institut National de Recherche en Informatique et Automatique, Inria Saclay, Palaiseau, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microtubules and their post-translational modifications are involved in major cellular processes. In severe diseases such as neurodegenerative disorders, tyrosinated tubulin and tyrosinated microtubules are in lower concentration. We present here a mechanistic mathematical model of the microtubule tyrosination cycle combining computational modeling and high-content image analyses to understand the key kinetic parameters governing the tyrosination status in different cellular models. That mathematical model is parameterized, firstly, for neuronal cells using kinetic values taken from the literature, and, secondly, for proliferative cells, by a change of two parameter values obtained, and shown minimal, by a continuous optimization procedure based on temporal logic constraints to formalize experimental high-content imaging data. In both cases, the mathematical models explain the inability to increase the tyrosination status by activating the Tubulin Tyrosine Ligase enzyme. The tyrosinated tubulin is indeed the product of a chain of two reactions in the cycle: the detyrosinated microtubule depolymerization followed by its tyrosination. The tyrosination status at equilibrium is thus limited by both reaction rates and activating the tyrosination reaction alone is not effective. Our computational model also predicts the effect of inhibiting the Tubulin Carboxy Peptidase enzyme which we have experimentally validated in MEF cellular model. Furthermore, the model predicts that the activation of two particular kinetic parameters, the tyrosination and detyrosinated microtubule depolymerization rate constants, in synergy, should suffice to enable an increase of the tyrosination status in living cells.

Indexed as

TubulinTyrosineDrug Evaluation, PreclinicalMicrotubulesModels, TheoreticalTubulinTyrosine

Identifiers

PMID35759459
PMCPMC9236252

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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 OpenQuestion graph.