Evidence map›Paper›PMID 27162210›Full record

ArticlePathogens and disease2016

Characterizing the transcriptional adaptation of Staphylococcus aureus to stationary phase growth.

Andy Weiss, William H Broach, Lindsey N Shaw

Open access · bronzeAbstract read
In one paragraph

Article in Pathogens and disease, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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.

Andy WeissDepartment of Cell Biology, Microbiology and Molecular Biology, University of South Florida, Tampa, FL 33620, USA.
William H BroachDepartment of Cell Biology, Microbiology and Molecular Biology, University of South Florida, Tampa, FL 33620, USA.
Lindsey N ShawDepartment of Cell Biology, Microbiology and Molecular Biology, University of South Florida, Tampa, FL 33620, USA shaw@usf.edu.
University of South Florida · US

Funding

Characterization of ??S in the stress & virulence responses of S. aureusR01AI080626 · NIAID · UNIVERSITY OF SOUTH FLORIDA · PI SHAW, LINDSEY NEIL · 2010 to 2013
$1.3M
NIAID NIH HHS R01 AI080626
6 · The paper itself

Abstract

Staphylococcus aureus is an important human pathogen that causes life-threatening infections, and is resistant to the majority of our antibiotic arsenal. This resistance is complicated by the observation that most antibacterial agents target actively growing cells, thus, proving ineffective against slow growing populations, such as cells within a biofilm or in stationary phase. Recently, our group generated updated genome annotation files for S. aureus that not only include protein-coding genes but also regulatory and small RNAs. As such, these annotation files were used to perform a transcriptomic analysis in order to understand the metabolic and physiological changes that occur during transition from active growth to stationary phase; with a focus on sRNAs. We observed ∼24% of protein-coding and 34% of sRNA genes displaying changes in expression by ≥3-fold. Collectively, this study adds to our understanding of S. aureus adaptation to nutrient-limiting conditions, and sheds new light onto the contribution of sRNAs to this process.

Indexed as

Adaptation, BiologicalGene Expression Regulation, BacterialTranscription, GeneticGene Expression ProfilingStaphylococcus aureusTranscriptomebiofilmRNAseqRNA-sequencingsmall RNAsRNAStaphylococcus aureusstationary phasetranscriptional regulation

Identifiers

PMID27162210
PMCPMC5985488
OpenAlexW2371036461

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.