Evidence map›Paper›PMID 35469420›Full record

ArticlemSystems2022

Genome-Wide Identification of

Sardar Karash, Timothy L Yahr

Open access · goldAbstract read
In one paragraph

Article in mSystems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

10 citing papers in PubMed, 14 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

2 authors at 1 institution in 1 country.

Sardar KarashDepartment of Microbiology and Immunology, University of Iowagrid.214572.7, Iowa City, Iowa, USA.
Timothy L YahrDepartment of Microbiology and Immunology, University of Iowagrid.214572.7, Iowa City, Iowa, USA.ORCID 0000-0001-9054-8704
University of Iowa · US

Funding

Vector Core-Core 2P30DK054759 · NIDDK · UNIVERSITY OF IOWA · PI Amy Leanne Ryan · 1998 to 2026
$30.5M
NIDDK NIH HHS P30 DK054759
6 · The paper itself

Abstract

Pseudomonas aeruginosa is an opportunistic pathogen prevalent in the environment and in health care settings. Transmission in the health care setting occurs through human-human interactions and/or contact with contaminated surfaces. Moist surfaces such as respirators, sink and tub drains, and even disinfectants can serve as reservoirs. Dry surfaces such as plastic and stainless steel could also serve as a reservoir but would necessitate some degree of tolerance to desiccation. Using an assay to measure P. aeruginosa tolerance to desiccation on plastic and stainless-steel surfaces, we found that only 0.05 to 0.1% of the desiccated cells could be recovered 24 h postdesiccation. We took advantage of the strong selection imposed by desiccation to identify genes important for tolerance using Tn-seq. A highly saturated Tn-seq library was desiccated on plastic and stainless-steel surfaces. NexGen sequencing of the recovered cells identified 97 genes important for survival. Comparing cells desiccated under low- and high-nutrient conditions allowed for differentiation of genes important for desiccation tolerance. The 53 genes identified in the latter analysis are involved in maintenance of cell envelope integrity, purine and pyrimidine biosynthesis, tricarboxylic acid (TCA) cycle, and the hydrolysis of misfolded proteins. The Tn-seq findings were validated by competition experiments with wild-type (WT) cells and select Tn insertion mutants. Mutants lacking

Indexed as

DesiccationPseudomonas aeruginosaGene LibraryHumansPlasticsSteelPlasticsSteelcell envelopedesiccationPseudomonas aeruginosapyrimidinereservoirstress responsesTn-seq

Identifiers

PMID35469420
PMCPMC9239045
OpenAlexW4224942192

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.