Evidence map›Paper›PMID 24661178›Full record

ArticleFEMS microbiology letters2014

Antibacterial enzymes from the functional screening of metagenomic libraries hosted in Ralstonia metallidurans.

Hala A Iqbal, Jeffrey W Craig, Sean F Brady

Open access · bronzeAbstract read
In one paragraph

Article in FEMS microbiology letters, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

15 citing papers in PubMed, 37 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.

Hala A IqbalLaboratory of Genetically Encoded Small Molecules, Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA.
Jeffrey W Craig
Sean F Brady
Howard Hughes Medical Institute · US

Funding

Weill Cornell/Rockefeller/Sloan-Kettering MST ProgramT32GM007739 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI HSU, KATHARINE C · 1985 to 2023
$51.1M
Discovery and characterization of new natural products from uncultured bacteriaR01GM077516 · NIGMS · ROCKEFELLER UNIVERSITY · PI BRADY, SEAN F · 2006 to 2014
$3.0M
Howard Hughes Medical InstituteNIGMS NIH HHS GM077516NIGMS NIH HHS R01 GM077516NIGMS NIH HHS T32 GM007739
6 · The paper itself

Abstract

Phenotype-based screening of bacterial metagenomic libraries provides an avenue for the discovery of novel genes, enzymes, and metabolites that have a variety of potential clinical and industrial uses. Here, we report the identification of a functionally diverse collection of antibacterially active enzymes from the phenotypic screening of 700 000 cosmid clones prepared from Arizona soil DNA and hosted in Ralstonia metallidurans. Environmental DNA clones surrounded by zones of growth inhibition in a bacterial overlay assay were found, through bioinformatics and functional analyses, to encode enzymes with predicted peptidase, lipase, and glycolytic activities conferring antibiosis. The antibacterial activities observed in our R. metallidurans-based assay could not be replicated with the same clones in screens using Escherichia coli as a heterologous host, suggesting that the large-scale screening of metagenomic libraries for antibiosis using phylogenetically diverse hosts should be a productive strategy for identifying enzymes with functionally diverse antibacterial activities.

Indexed as

AntibiosisMetagenomicsSoil MicrobiologyBacterial ProteinsGene LibraryGenome, BacterialMolecular Sequence DataPhylogenyRalstoniaBacterial ProteinseDNAmetagenomicsoil

Identifiers

PMID24661178
PMCPMC4028719
OpenAlexW1984201842

What OpenQuestion holds

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LicenceTDM
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.