Evidence map›Paper›PMID 18495030›Full record

ArticleBMC genomics2008

Simultaneous gene expression profiling in human macrophages infected with Leishmania major parasites using SAGE.

Fatma Z Guerfali, Dhafer Laouini, Lamia Guizani-Tabbane, Florence Ottones, Khadija Ben-Aissa, Alia Benkahla, Laurent Manchon, David Piquemal, Sondos Smandi, Ons Mghirbi and 3 more

Abstract read
In one paragraph

Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
–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

40 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Frontiers in immunology · 2023
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  6. Frontiers in genetics · 2023
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  7. Review
  8. Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. miR-548d-3p Alters Parasite Growth and Inflammation inFrontiers in cellular and infection microbiology · 2021
    Article
  14. Advances in UnderstandingFrontiers in cell and developmental biology · 2021
    Review
  15. Review
  16. Article
  17. Review
  18. Model-based Evaluation of Gene Expression Changes in Response toGene regulation and systems biology · 2019
    Review
  19. RNA-Seq Revealed Expression of Many Novel Genes Associated WithFrontiers in cellular and infection microbiology · 2019
    Article
  20. 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

13 authors.

Fatma Z GuerfaliLaboratoire d'Immuno-Pathologie, Vaccinologie et Génétique Moléculaire, WHO Collaborating Center for Research and Training in Leishmaniasis, Institut Pasteur de Tunis, 13 place Pasteur, BP 74, 1002 Tunis-Belvédère, Tunisia. fzguerfali@yahoo.fr
Dhafer Laouini
Lamia Guizani-Tabbane
Florence Ottones
Khadija Ben-Aissa
Alia Benkahla
Laurent Manchon
David Piquemal
Sondos Smandi
Ons Mghirbi
Thérèse Commes
Jacques Marti
Koussay Dellagi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLeishmania (L) are intracellular protozoan parasites that are able to survive and replicate within the harsh and potentially hostile phagolysosomal environment of mammalian mononuclear phagocytes. A complex interplay then takes place between the macrophage (MPhi) striving to eliminate the pathogen and the parasite struggling for its own survival. To investigate this host-parasite conflict at the transcriptional level, in the context of monocyte-derived human MPhis (MDM) infection by L. major metacyclic promastigotes, the quantitative technique of serial analysis of gene expression (SAGE) was used.

resultsAfter extracting mRNA from resting human MPhis, Leishmania-infected human MPhis and L. major parasites, three SAGE libraries were constructed and sequenced generating up to 28,173; 57,514 and 33,906 tags respectively (corresponding to 12,946; 23,442 and 9,530 unique tags). Using computational data analysis and direct comparison to 357,888 publicly available experimental human tags, the parasite and the host cell transcriptomes were then simultaneously characterized from the mixed cellular extract, confidently discriminating host from parasite transcripts. This procedure led us to reliably assign 3,814 tags to MPhis' and 3,666 tags to L. major parasites transcripts. We focused on these, showing significant changes in their expression that are likely to be relevant to the pathogenesis of parasite infection: (i) human MPhis genes, belonging to key immune response proteins (e.g., IFNgamma pathway, S100 and chemokine families) and (ii) a group of Leishmania genes showing a preferential expression at the parasite's intra-cellular developing stage.

conclusionDual SAGE transcriptome analysis provided a useful, powerful and accurate approach to discriminating genes of human or parasitic origin in Leishmania-infected human MPhis. The findings presented in this work suggest that the Leishmania parasite modulates key transcripts in human MPhis that may be beneficial for its establishment and survival. Furthermore, these results provide an overview of gene expression at two developmental stages of the parasite, namely metacyclic promastigotes and intracellular amastigotes and indicate a broad difference between their transcriptomic profiles. Finally, our reported set of expressed genes will be useful in future rounds of data mining and gene annotation.

Indexed as

AnimalsApoptosisBase SequenceChemokinesExtracellular SpaceGene Expression ProfilingGene Expression RegulationGene LibraryGenes, MHC Class IGenes, MHC Class IIHost-Parasite InteractionsHumansInterferon-gammaIntracellular SpaceLeishmania majorLeishmaniasis, CutaneousChemokinesInterferon-gammaRNA, MessengerS100 Proteins

Identifiers

PMID18495030
PMCPMC2430024

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LicenceCC BY
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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.