Evidence map›Paper›PMID 37905091›Full record

ArticlebioRxiv : the preprint server for biology2023

T-cell commitment inheritance - an agent-based multi-scale model.

Emil Andersson, Ellen V Rothenberg, Carsten Peterson, Victor Olariu

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Emil AnderssonComputational Biology and Biological Physics, Centre for Environmental and Climate Science, Lund University, Lund, Sweden.
Ellen V RothenbergDivision of Biology and Biological Engineering, 156-29, California Institute of Technology, Pasadena, CA 91125, USA.
Carsten PetersonComputational Biology and Biological Physics, Centre for Environmental and Climate Science, Lund University, Lund, Sweden.
Victor OlariuComputational Biology and Biological Physics, Centre for Environmental and Climate Science, Lund University, Lund, Sweden.

Funding

Kinetic modeling and single-cell molecular mechanisms of early T-cell commitmentR01HL119102 · NHLBI · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI PETERSON, CARSTEN, ROTHENBERG, ELLEN V. · 2014 to 2018
$3.0M
NHLBI NIH HHS R01 HL119102
6 · The paper itself

Abstract

T-cell development provides an excellent model system for studying lineage commitment from a multipotent progenitor. The intrathymic development process has been thoroughly studied. The molecular circuitry controlling it has been dissected and the necessary steps like programmed shut off of progenitor genes and T-cell genes upregulation have been revealed. However, the exact timing between decision-making and commitment stage remains unexplored. To this end, we implemented an agent-based multi-scale model to investigate inheritance in early T-cell development. Treating each cell as an agent provides a powerful tool as it tracks each individual cell of a simulated T-cell colony, enabling the construction of lineage trees. Based on the lineage trees, we introduce the concept of the last common ancestors (LCA) of committed cells and analyse their relations, both at single-cell level and population level. In addition to simulating wild-type development, we also conduct knockdown analysis. Our simulations showed that the commitment is a three-step process over several cell generations where a cell is first prepared by a transcriptional switch. This is followed by the loss of the Bcl11b-opposing function two to three generations later which is when the decision to commit is taken. Finally, after another one to two generations, the cell becomes committed by transitioning to the DN2b state. Our results showed that there is inheritance in the commitment mechanism.

Identifiers

PMID37905091
PMCPMC10614897

What OpenQuestion holds

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LicenceCC BY-ND
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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.