Evidence map›Paper›PMID 27557669›Full record

ArticleBMC biotechnology2016

Characterization of transcription factor response kinetics in parallel.

Betul Bilgin, Aritro Nath, Christina Chan, S Patrick Walton

Open access · goldAbstract read
In one paragraph

Article in BMC biotechnology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

4 authors at 1 institution in 1 country.

Betul BilginDepartment of Chemical Engineering and Materials Science, Michigan State University, 428 S. Shaw Lane, Room 3249, Engineering Building, East Lansing, MI, 48824-1226, USA.
Aritro NathGenetics Program, Michigan State University, East Lansing, MI, 48824, USA.
Christina ChanDepartment of Chemical Engineering and Materials Science, Michigan State University, 428 S. Shaw Lane, Room 3249, Engineering Building, East Lansing, MI, 48824-1226, USA.
S Patrick WaltonDepartment of Chemical Engineering and Materials Science, Michigan State University, 428 S. Shaw Lane, Room 3249, Engineering Building, East Lansing, MI, 48824-1226, USA. spwalton@egr.msu.edu.
Michigan State University · US

Funding

Develop a Dynamic Model that Incoporates Text-mining to Reconstruct NetworksR01GM079688 · NIGMS · MICHIGAN STATE UNIVERSITY · PI CHAN, CHRISTINA · 2007 to 2012
$1.2M
Maximizing siRNA Function through Mechanism-based Sequence and Vehicle DesignR01GM089866 · NIGMS · MICHIGAN STATE UNIVERSITY · PI WALTON, STEPHEN PATRICK · 2010 to 2013
$922k
Development of a parallel, array-based transcription factor expression assayR21RR024439 · NCRR · MICHIGAN STATE UNIVERSITY · PI WALTON, STEPHEN PATRICK · 2008 to 2010
$540k
Phenotype-Targeted Inference of Flux-Enzyme Correlations in Adipocyte MetabolismR56DK081768 · NIDDK · TUFTS UNIVERSITY MEDFORD · PI LEE, KYONGBUM · 2010 to 2011
$489k
Engineering an in vitro model of adipose tissue formation and metabolismR56DK088251 · NIDDK · TUFTS UNIVERSITY MEDFORD · PI LEE, KYONGBUM · 2010 to 2010
$205k
NCRR NIH HHS R21 RR024439NIDDK NIH HHS R56 DK081768NIDDK NIH HHS R56 DK088251NIGMS NIH HHS R01 GM079688NIGMS NIH HHS R01 GM089866
6 · The paper itself

Abstract

backgroundTranscription factors (TFs) are effectors of cell signaling pathways that regulate gene expression. TF networks are highly interconnected; one signal can lead to changes in many TF levels, and one TF level can be changed by many different signals. TF regulation is central to normal cell function, with altered TF function being implicated in many disease conditions. Thus, measuring TF levels in parallel, and over time, is crucial for understanding the impact of stimuli on regulatory networks and on diseases.

resultsHere, we report the parallel analysis of temporal TF level changes due to multiple stimuli in distinct cell types. We have analyzed short-term dynamic changes in the levels of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB), signal transducer and activator of transcription 3 (Stat3), cAMP response element-binding protein (CREB), glucocorticoid receptor (GR), and TATA binding protein (TBP), in breast and liver cancer cells after tumor necrosis factor-alpha (TNF-α) and palmitic acid (PA) exposure. In response to both stimuli, NF-kB and CREB levels were increased, Stat3 decreased, and TBP was constant. GR levels were unchanged in response to TNF-α stimulation and increased in response to PA treatment.

conclusionsOur results show significant overlap in signaling initiated by TNF-α and by PA, with the exception that the events leading to PA-mediated cytotoxicity likely also include induction of GR signaling. These results further illuminate the dynamics of TF responses to cytokine and fatty acid exposure, while concomitantly demonstrating the utility of parallel TF measurement approaches in the analysis of biological phenomena.

Indexed as

Gene Expression ProfilingHep G2 CellsHumansKineticsMetabolic Clearance RateNeoplasm ProteinsNeoplasms, ExperimentalSignal TransductionTranscription FactorsTranscriptomeNeoplasm ProteinsTranscription FactorsHepG2 cellsKineticsMDA-MB-231 cellsPalmitic acid treatmentParallelTranscription factors

Identifiers

PMID27557669
PMCPMC4997724
OpenAlexW2513815921

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.