Evidence map›Paper›PMID 22381171›Full record

ArticleThe Journal of surgical research2012

Dynamics of hepatic gene expression profile in a rat cecal ligation and puncture model.

Qian Yang, John S A Mattick, Mehmet A Orman, Tung T Nguyen, Marianthi G Ierapetritou, Francois Berthiaume, Ioannis P Androulakis

Open access · greenAbstract read
In one paragraph

Article in The Journal of surgical research, 2012. 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
0.6field-weighted citation impact, top 33% 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, 15 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Liver - guardian, modifier and target of sepsis.Nature reviews. Gastroenterology & hepatology · 2017
    Review
  6. Article
  7. mRNA Expression of Ovine Angiopoietin-like Protein 4 Gene in Adipose Tissues.Asian-Australasian journal of animal sciences · 2016
    Article
  8. Article
  9. Accounting for the delay in the transition from acute to chronic pain: axonal and nuclear mechanisms.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2015
    Article
  10. Article
  11. 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

7 authors at 2 institutions in 1 country.

Qian YangChemical and Biochemical Engineering Department, Rutgers University, Piscataway, New Jersey 08854, USA.
John S A Mattick
Mehmet A Orman
Tung T Nguyen
Marianthi G Ierapetritou
Francois Berthiaume
Ioannis P Androulakis
Rutgers, The State University of New Jersey · USQuantitative BioSciences · US

Funding

Bioinformatics Analysis of Control Mechanisms of HypermetabolismR01GM082974 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI ANDROULAKIS, IOANNIS P · 2008 to 2011
$1.6M
NIGMS NIH HHS GM082974NIGMS NIH HHS R01 GM082974
6 · The paper itself

Abstract

backgroundSepsis remains a major clinical challenge in intensive care units. The difficulty in developing new and more effective treatments for sepsis exemplifies our incomplete understanding of the underlying pathophysiology of it. One of the more widely used rodent models for studying polymicrobial sepsis is cecal ligation and puncture (CLP). While a number of CLP studies investigated the ensuing systemic inflammatory response, they usually focus on a single time point post-CLP and therefore fail to describe the dynamics of the response. Furthermore, previous studies mostly use surgery without infection (herein referred to as sham CLP, SCLP) as a control for the CLP model, however, SCLP represents an aseptic injurious event that also stimulates a systemic inflammatory response. Thus, there is a need to better understand the dynamics and expression patterns of both injury- and sepsis-induced gene expression alterations to identify potential regulatory targets. In this direction, we characterized the response of the liver within the first 24 h in a rat model of SCLP and CLP using a time series of microarray gene expression data.

methodsRats were randomly divided into three groups: sham, SCLP, and CLP. Rats in SCLP group are subjected to laparotomy, cecal ligation, and puncture while those in CLP group are subjected to the similar procedures without cecal ligation and puncture. Animals were saline resuscitated and sacrificed at defined time points (0, 2, 4, 8, 16, and 24 h). Liver tissues were explanted and analyzed for their gene expression profiles using microarray technology. Unoperated animals (Sham) serve as negative controls. After identifying differentially expressed probesets between sham and SCLP or CLP conditions over time, the concatenated data sets corresponding to these differentially expressed probesets in sham and SCLP or CLP groups were combined and analyzed using a "consensus clustering" approach. Promoters of genes that share common characteristics were extracted and compared with gene batteries comprised of co-expressed genes to identify putatative transcription factors, which could be responsible for the co-regulation of those genes.

resultsThe SCLP/CLP genes whose expression patterns significantly changed compared with sham over time were identified, clustered, and finally analyzed for pathway enrichment. Our results indicate that both CLP and SCLP triggered the activation of a proinflammatory response, enhanced synthesis of acute-phase proteins, increased metabolism, and tissue damage markers. Genes triggered by CLP, which can be directly linked to bacteria removal functions, were absent in SCLP injury. In addition, genes relevant to oxidative stress induced damage were unique to CLP injury, which may be due to the increased severity of CLP injury versus SCLP injury. Pathway enrichment identified pathways with similar functionality but different dynamics in the two injury models, indicating that the functions controlled by those pathways are under the influence of different transcription factors and regulatory mechanisms. Putatively identified transcription factors, notably including cAMP response element-binding (CREB), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), and signal transducer and activator of transcription (STAT), were obtained through analysis of the promoter regions in the SCLP/CLP genes. Our results show that while transcription factors such as NF-κB, homeodomain transcription factor (HOMF), and GATA transcription factor (GATA) were common in both injuries for the IL-6 signaling pathway, there were many other transcription factors associated with that pathway which were unique to CLP, including forkhead (FKHD), hairy/enhancer of split family (HESF), and interferon regulatory factor family (IRFF). There were 17 transcription factors that were identified as important in at least two pathways in the CLP injury, but only seven transcription factors with that property in the SCLP injury. This also supports the hypothesis of unique regulatory modules that govern the pathways present in both the CLP and SCLP response.

conclusionsBy using microarrays to assess multiple genes in a high throughput manner, we demonstrate that an inflammatory response involving different dynamics and different genes is triggered by SCLP and CLP. From our analysis of the CLP data, the key characteristics of sepsis are a proinflammatory response, which drives hypermetabolism, immune cell activation, and damage from oxidative stress. This contrasts with SCLP, which triggers a modified inflammatory response leading to no immune cell activation, decreased detoxification potential, and hyper metabolism. Many of the identified transcription factors that drive the CLP-induced response are not found in the SCLP group, suggesting that SCLP and CLP induce different types of inflammatory responses via different regulatory pathways.

Indexed as

Gene Expression ProfilingAnimalsCecumDisease Models, AnimalGene Expression RegulationInflammationLigationLiverMaleOligonucleotide Array Sequence AnalysisRatsRats, Sprague-DawleySepsisTranscription FactorsWounds, StabTranscription Factors

Identifiers

PMID22381171
PMCPMC3368040
OpenAlexW2075866769

What OpenQuestion holds

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Read underepoch 390

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.