Evidence map›Paper›PMID 31208443›Full record

ArticleCell communication and signaling : CCS2019

Novel interconnections of HOG signaling revealed by combined use of two proteomic software packages.

Marion Janschitz, Natalie Romanov, Gina Varnavides, David Maria Hollenstein, Gabriela Gérecová, Gustav Ammerer, Markus Hartl, Wolfgang Reiter

Open access · goldAbstract read
In one paragraph

Article in Cell communication and signaling : CCS, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 12 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

8 authors at 3 institutions in 2 countries.

Marion JanschitzDepartment of Biochemistry, Max F. Perutz Laboratories, Vienna BioCenter, Vienna, Austria.
Natalie RomanovStructural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117, Heidelberg, Germany.
Gina VarnavidesMass Spectrometry Facility, Max F. Perutz Laboratories, University of Vienna, Vienna BioCenter, Vienna, Austria.
David Maria HollensteinDepartment of Biochemistry, Max F. Perutz Laboratories, Vienna BioCenter, Vienna, Austria.
Gabriela GérecováDepartment of Biochemistry, Max F. Perutz Laboratories, Vienna BioCenter, Vienna, Austria.
Gustav AmmererDepartment of Biochemistry, Max F. Perutz Laboratories, Vienna BioCenter, Vienna, Austria.
Markus HartlDepartment of Biochemistry, Max F. Perutz Laboratories, Vienna BioCenter, Vienna, Austria.
Wolfgang ReiterMass Spectrometry Facility, Max F. Perutz Laboratories, University of Vienna, Vienna BioCenter, Vienna, Austria. wolfgang.l.reiter@univie.ac.at.ORCID 0000-0003-1266-8975
Max Perutz Labs · ATUniversity of Vienna · ATMax Planck Institute of Biophysics · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern quantitative mass spectrometry (MS)-based proteomics enables researchers to unravel signaling networks by monitoring proteome-wide cellular responses to different stimuli. MS-based analysis of signaling systems usually requires an integration of multiple quantitative MS experiments, which remains challenging, given that the overlap between these datasets is not necessarily comprehensive. In a previous study we analyzed the impact of the yeast mitogen-activated protein kinase (MAPK) Hog1 on the hyperosmotic stress-affected phosphorylome. Using a combination of a series of hyperosmotic stress and kinase inhibition experiments, we identified a broad range of direct and indirect substrates of the MAPK. Here we re-evaluate this extensive MS dataset and demonstrate that a combined analysis based on two software packages, MaxQuant and Proteome Discoverer, increases the coverage of Hog1-target proteins by 30%. Using protein-protein proximity assays we show that the majority of new targets gained by this analysis are indeed Hog1-interactors. Additionally, kinetic profiles indicate differential trends of Hog1-dependent versus Hog1-independent phosphorylation sites. Our findings highlight a previously unrecognized interconnection between Hog1 signaling and the RAM signaling network, as well as sphingolipid homeostasis.

Indexed as

Signal TransductionSoftwareHeLa CellsHumansMitogen-Activated Protein KinasesPhosphorylationProteomicsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsHOG1 protein, S cerevisiaeMitogen-Activated Protein KinasesSaccharomyces cerevisiae ProteinsHigh-osmolarity glycerol (HOG)Hog1Hyperosmotic stress responseKic1MaxQuantMitogen-activated protein kinase (MAPK)Orm2ORMDLp38Proteome discovererProteomics

Identifiers

PMID31208443
PMCPMC6572760
OpenAlexW2951120821

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.