Evidence map›Paper›PMID 28454561›Full record

ArticleBMC genomics2017

A comprehensive multi-omics approach uncovers adaptations for growth and survival of Pseudomonas aeruginosa on n-alkanes.

Sarah L Grady, Stephanie A Malfatti, Thusitha S Gunasekera, Brian K Dalley, Matt G Lyman, Richard C Striebich, Michael B Mayhew, Carol L Zhou, Oscar N Ruiz, Larry C Dugan

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

16 citing papers in PubMed, 30 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

10 authors at 5 institutions in 1 country.

Sarah L GradyBiosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, 94550, USA. grady7@llnl.gov.
Stephanie A MalfattiBiosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, 94550, USA.
Thusitha S GunasekeraEnvironmental Microbiology Group, University of Dayton Research Institute, University of Dayton, Dayton, OH, 45469, USA.
Brian K DalleyHuntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT, 84112, USA.
Matt G LymanBiosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, 94550, USA.
Richard C StriebichEnvironmental Microbiology Group, University of Dayton Research Institute, University of Dayton, Dayton, OH, 45469, USA.
Michael B MayhewComputational Engineering Division, Lawrence Livermore National Laboratory, Livermore, CA, 94550, USA.
Carol L ZhouComputing Applications and Research Department, Global Security Computing and Applications Division, Lawrence Livermore National Laboratory, Livermore, CA, 94550, USA.
Oscar N RuizFuels and Energy Branch, Aerospace Systems Directorate, Air Force Research Laboratory, Wright-Patterson AFB, OH, 45433, USA.
Larry C DuganBiosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, 94550, USA.
Lawrence Livermore National Laboratory · USUniversity of Dayton · USHuntsman Cancer Institute · USLawrence Livermore National Security · USUnited States Air Force Research Laboratory · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExamination of complex biological systems has long been achieved through methodical investigation of the system's individual components. While informative, this strategy often leads to inappropriate conclusions about the system as a whole. With the advent of high-throughput "omic" technologies, however, researchers can now simultaneously analyze an entire system at the level of molecule (DNA, RNA, protein, metabolite) and process (transcription, translation, enzyme catalysis). This strategy reduces the likelihood of improper conclusions, provides a framework for elucidation of genotype-phenotype relationships, and brings finer resolution to comparative genomic experiments. Here, we apply a multi-omic approach to analyze the gene expression profiles of two closely related Pseudomonas aeruginosa strains grown in n-alkanes or glycerol.

resultsThe environmental P. aeruginosa isolate ATCC 33988 consumed medium-length (C

conclusionThis work represents the first time results from RNA-seq, microarray, ribosome footprinting, proteomics, and small molecule LC-MS experiments have been integrated to compare gene expression in bacteria. Together, these data provide insights as to why strain ATCC 33988 is better adapted for growth and survival on n-alkanes.

Indexed as

AlkanesComputational BiologyGene Expression ProfilingGlycolipidsPseudomonas aeruginosaQuorum SensingAlkanesGlycolipidsrhamnolipidAlkane degradationMulti-omicsPseudomonas aeruginosaQuorum sensingRibosome footprinting

Identifiers

PMID28454561
PMCPMC5410065
OpenAlexW2608253565

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.