Evidence map›Paper›PMID 31370875›Full record

ArticleBMC research notes2019

Label-free quantitative proteomics in Candida yeast species: technical and biological replicates to assess data reproducibility.

Gaëlle Lelandais, Thomas Denecker, Camille Garcia, Nicolas Danila, Thibaut Léger, Jean-Michel Camadro

Open access · goldAbstract read
In one paragraph

Article in BMC research notes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 44% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Omics Analyses: How to Navigate Through a Constant Data Deluge.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  2. Article
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

6 authors at 2 institutions in 1 country.

Gaëlle LelandaisCEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Univ. Paris-Sud, Gif-Sur-Yvette, France. gaelle.lelandais@u-psud.fr.ORCID http://orcid.org/0000-0002-2842-6172
Thomas DeneckerCEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Univ. Paris-Sud, Gif-Sur-Yvette, France.
Camille GarciaMass Spectrometry Laboratory, CNRS, Institut Jacques Monod, UMR 7592, Université de Paris, 75205, Paris, France.
Nicolas DanilaCNRS, Institut Jacques Monod (IJM), Univ. Paris Diderot, Paris, France.
Thibaut LégerMass Spectrometry Laboratory, CNRS, Institut Jacques Monod, UMR 7592, Université de Paris, 75205, Paris, France.
Jean-Michel CamadroMass Spectrometry Laboratory, CNRS, Institut Jacques Monod, UMR 7592, Université de Paris, 75205, Paris, France.
Centre National de la Recherche Scientifique · FRUniversité Paris-Sud · FR

Funding

Agence Nationale de la Recherche ANR-14-CE14-0018-02
6 · The paper itself

Abstract

objectiveLabel-free quantitative proteomics has emerged as a powerful strategy to obtain high quality quantitative measures of the proteome with only a very small quantity of total protein extract. Because our research projects were requiring the application of bottom-up shotgun mass spectrometry proteomics in the pathogenic yeasts Candida glabrata and Candida albicans, we performed preliminary experiments to (i) obtain a precise list of all the proteins for which measures of abundance could be obtained and (ii) assess the reproducibility of the results arising respectively from biological and technical replicates. DATA DESCRIPTION: Three time-courses were performed in each Candida species, and an alkaline pH stress was induced for two of them. Cells were collected 10 and 60 min after stress induction and proteins were extracted. Samples were analysed two times by mass spectrometry. Our final dataset thus comprises label-free quantitative proteomics results for 24 samples (two species, three time-courses, two time points and two runs of mass spectrometry). Statistical procedures were applied to identify proteins with differential abundances between stressed and unstressed situations. Considering that C. glabrata and C. albicans are human pathogens, which face important pH fluctuations during a human host infection, this dataset has a potential value to other researchers in the field.

Indexed as

Candida albicansCandida glabrataDatasets as TopicFungal ProteinsHydrogen-Ion ConcentrationInformation DisseminationInternetProteomeProteomicsStress, PhysiologicalFungal ProteinsProteomeAlkaline pHCandida albicansCandida glabrataLabel-free quantitative proteomicsMass spectrometry

Identifiers

PMID31370875
PMCPMC6669970
OpenAlexW2966220454

What Socratic 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 Socratic graph.