Evidence map›Paper›PMID 23934352›Full record

ArticleCurrent microbiology2014

Time-related transcriptome analysis of B. subtilis 168 during growth with glucose.

Chun-Kai Yang, Phang C Tai, Chung-Dar Lu

Abstract read
PubMed Publisher
In one paragraph

Article in Current microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Glucose Induces ECF Sigma Factor Genes,Frontiers in microbiology · 2016
    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

3 authors at 1 institution in 1 country.

Chun-Kai YangDepartment of Biology, Georgia State University, 161 Jesse Hill Drive, Atlanta, GA, 30303, USA.
Phang C Tai
Chung-Dar Lu
Georgia State University · US

Funding

PROTEIN TRANSLOCATION &EXPORT IN GRAM-NEGATIVE BACTERIAR01GM034766 · NIGMS · GEORGIA STATE UNIVERSITY · PI TAI, PHANG C. · 1985 to 2005
$2.5M
NIGMS NIH HHS GM 34766
6 · The paper itself

Abstract

Gene expression in Bacillus subtilis from late exponential to stationary phase was monitored by DNA microarrays with samples taken from the culture in LB broth with glucose supplement to prevent sporulation. Three major patterns of gene expression as revealed in this study were consistent to the expression profiling of PerR/Spx regulons and three major sigma factors-SigA, SigB, and SigW. Expression of most SigA-dependent house-keeping genes was significantly decreased and remained at low levels in the stationary phase. The sigB gene and additional genes of the SigB regulon for stress response exhibited a distinct pattern of transient induction with a peak in transition phase. The majority of induced genes after cessation of SigB-dependent surge were subjected to regulation by SigW, PerR, and Spx in response to oxidative stress. No induction of spo0A and skfA regulons supports the suppression of sporulation and cannibalism processes in the stationary phase by glucose supplement. In summary, these results depicted complicated strategies by cells to adapt changes from the fast growing exponential phase toward the stationary phase. The absence of programmed cell death and sporulation greatly facilitated data analysis and the identification of distinct expression patterns in the stationary phase of growth in B. subtilis.

Indexed as

Bacillus subtilisGene Expression ProfilingGene Expression Regulation, BacterialGlucoseOligonucleotide Array Sequence AnalysisTranscriptomeGlucose

Identifiers

PMID23934352
OpenAlexW1974077300

What OpenQuestion holds

Textmetadata
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.