Evidence map›Paper›PMID 21695480›Full record

ArticleChromosoma2011

Transcriptomic and nuclear architecture of immune cells after LPS activation.

Romain Solinhac, Florence Mompart, Pascal Martin, David Robelin, Philippe Pinton, Eddie Iannuccelli, Yvette Lahbib-Mansais, Isabelle P Oswald, Martine Yerle-Bouissou

Abstract read
PubMed Publisher
In one paragraph

Article in Chromosoma, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

11 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. Article
  3. The importance of the nuclear positioning of the PPARG gene for its expression during porcine in vitro adipogenesis.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2019
    Article
  4. Chromosome positioning and male infertility: it comes with the territory.Journal of assisted reproduction and genetics · 2018
    Review
  5. Review
  6. Article
  7. Current transcriptomics in pig immunity research.Mammalian genome : official journal of the International Mammalian Genome Society · 2015
    Review
  8. Article
  9. Article
  10. Article
  11. Visualization of the spatial positioning of the SNRPN, UBE3A, and GABRB3 genes in the normal human nucleus by three-color 3D fluorescence in situ hybridization.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2012
    Article
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

9 authors at 3 institutions in 1 country.

Romain SolinhacLaboratoire de Génétique Cellulaire, INRA, Castanet-Tolosan, France. romain.solinhac@toulouse.inra.fr
Florence Mompart
Pascal Martin
David Robelin
Philippe Pinton
Eddie Iannuccelli
Yvette Lahbib-Mansais
Isabelle P Oswald
Martine Yerle-Bouissou
Génétique Physiologie et Systèmes d'Elevage · FRToxalim Research Centre in Food Toxicology · FRLaboratoire de Génétique Cellulaire · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Changes in the nuclear positioning of specific genes, depending on their expression status, have been observed in a large diversity of physiological processes. However, gene position is poorly documented for immune cells which have been subjected to activation following bacterial infection. Using a pig model, we focused our study on monocyte-derived macrophages and neutrophils, as they are the first lines of defence against pathogens. We examined whether changes in gene expression due to LPS activation imply that genes have repositioned in the nuclear space. We first performed a transcriptomic analysis to identify the differentially expressed genes and then analysed the networks involved during lypopolysaccharide/interferon gamma activation in monocyte-derived macrophages. This allowed us to select four up-regulated (IL1β, IL8, CXCL10 and TNFα) and four down-regulated (VIM, LGALS3, TUBA3 and IGF2) genes. Their expression statuses were verified by quantitative real-time RT-PCR before studying their behaviour in the nuclear space during macrophage activation by means of 3D fluorescence in situ hybridization. No global correlation was found between gene activity and radial positioning. Only TNFα belonging to the highly transcribed MHC region on chromosome 7 became more peripherally localized in relation to the less decondensed state of its chromosome territory (CT) in activated macrophages. The analysis of gene positioning towards their CT revealed that IL8 increases significantly its tendency to be outside its CT during the activation process. In addition, the gene to CT edge distances increase for the three up-regulated genes (IL8, CXCL10 and TNFα) among the four analysed. Contrarily, the four down-regulated genes did not change their position. The analysis of gene behaviour towards their CT was extended to include neutrophils for three (TNFα, IL8 and IL1β) up- and two (IGF2 and TUBA3) down-regulated genes, and similar results were obtained. The analysis was completed by studying the four up-regulated genes in fibroblasts, not involved in immune response. Our data suggest that relocation in the nuclear space of genes that are differentially expressed in activated immune cells is gene and cell type specific but also closely linked to the entire up-regulation status of their chromosomal regions.

Indexed as

Gene Expression ProfilingAnimalsCell NucleusCells, CulturedCytokinesFemaleGene Expression RegulationLipopolysaccharidesMacrophage ActivationMacrophagesNeutrophil ActivationNeutrophilsSwineCytokinesLipopolysaccharides

Identifiers

PMID21695480
OpenAlexW2045388165

What OpenQuestion 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 OpenQuestion graph.