Evidence map›Paper›PMID 25350399›Full record

ArticlePloS one2014

An automated high-throughput cell-based multiplexed flow cytometry assay to identify novel compounds to target Candida albicans virulence-related proteins.

Stella M Bernardo, Christopher P Allen, Anna Waller, Susan M Young, Tudor Oprea, Larry A Sklar, Samuel A Lee

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Antifungal Drug Repurposing.Antibiotics (Basel, Switzerland) · 2020
    Article
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  4. Article
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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

7 authors at 2 institutions in 1 country.

Stella M BernardoSection of Infectious Diseases, New Mexico Veterans Healthcare System, Albuquerque, NM, United States of America; Division of Infectious Diseases, University of New Mexico Health Science Center, Albuquerque, NM, United States of America.
Christopher P AllenCenter for Molecular Discovery, University of New Mexico, Albuquerque, NM, United States of America.
Anna WallerCenter for Molecular Discovery, University of New Mexico, Albuquerque, NM, United States of America.
Susan M YoungCenter for Molecular Discovery, University of New Mexico, Albuquerque, NM, United States of America.
Tudor OpreaCenter for Molecular Discovery, University of New Mexico, Albuquerque, NM, United States of America.
Larry A SklarCenter for Molecular Discovery, University of New Mexico, Albuquerque, NM, United States of America.
Samuel A LeeSection of Infectious Diseases, New Mexico Veterans Healthcare System, Albuquerque, NM, United States of America; Division of Infectious Diseases, University of New Mexico Health Science Center, Albuquerque, NM, United States of America.
University of New Mexico · USNew Mexico VA Health Care System · US

Funding

Yeast Biology ConsortiumU54MH084690 · NIMH · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI TEGOS, GEORGE P · 2008 to 2013
$14.4M
BLRD VA I01 BX001130NIMH NIH HHS 1U54MH084690-01NIMH NIH HHS U54 MH084690
6 · The paper itself

Abstract

Although three major classes of systemic antifungal agents are clinically available, each is characterized by important limitations. Thus, there has been considerable ongoing effort to develop novel and repurposed agents for the therapy of invasive fungal infections. In an effort to address these needs, we developed a novel high-throughput, multiplexed screening method that utilizes small molecules to probe candidate drug targets in the opportunistic fungal pathogen Candida albicans. This method is amenable to high-throughput automated screening and is based upon detection of changes in GFP levels of individually tagged target proteins. We first selected four GFP-tagged membrane-bound proteins associated with virulence or antifungal drug resistance in C. albicans. We demonstrated proof-of-principle that modulation of fluorescence intensity can be used to assay the expression of specific GFP-tagged target proteins to inhibitors (and inducers), and this change is measurable within the HyperCyt automated flow cytometry sampling system. Next, we generated a multiplex of differentially color-coded C. albicans strains bearing C-terminal GFP-tags of each gene encoding candidate drug targets incubated in the presence of small molecules from the Prestwick Chemical Library in 384-well microtiter plate format. Following incubation, cells were sampled through the HyperCyt system and modulation of protein levels, as indicated by changes in GFP-levels of each strain, was used to identify compounds of interest. The hit rate for both inducers and inhibitors identified in the primary screen did not exceed 1% of the total number of compounds in the small-molecule library that was probed, as would be expected from a robust target-specific, high-throughput screening campaign. Secondary assays for virulence characteristics based on null mutant strains were then used to further validate specificity. In all, this study presents a method for the identification and verification of new antifungal drugs targeted to fungal virulence proteins using C. albicans as a model fungal pathogen.

Indexed as

High-Throughput Screening AssaysAntifungal AgentsCandida albicansFlow CytometryGene ExpressionGenes, ReporterHumansMicrobial Sensitivity TestsPhenotypeRecombinant Fusion ProteinsReproducibility of ResultsSmall Molecule LibrariesVirulenceAntifungal AgentsRecombinant Fusion ProteinsSmall Molecule Libraries

Identifiers

PMID25350399
PMCPMC4211665
OpenAlexW2059303071

What OpenQuestion holds

Textmetadata
LicenceCC0
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.