Evidence map›Paper›PMID 25401072›Full record

ArticleAMB Express2014

Subpopulation-proteomics reveal growth rate, but not cell cycling, as a major impact on protein composition in Pseudomonas putida KT2440.

Sarah Lieder, Michael Jahn, Jana Seifert, Martin von Bergen, Susann Müller, Ralf Takors

Open access · goldAbstract read
In one paragraph

Article in AMB Express, 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
1.6field-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

8 citing papers in PubMed, 16 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

6 authors at 2 institutions in 1 country.

Sarah LiederInstitute for Biochemical Engineering, University of Stuttgart, Allmandring 31, Stuttgart, Germany.
Michael JahnDepartment of Environmental Microbiology, Helmholtz Centre for Environmental Research-UFZ, Permoserstr. 15, Leipzig, 04318, Germany.
Jana SeifertDepartment of Proteomics, Helmholtz Centre for Environmental Research-UFZ, Permoserstr. 15, Leipzig, 04318, Germany ; Institute of Animal Nutrition, University of Hohenheim, Emil-Wolff-Straße 8 and 10, Stuttgart, 70599, Germany.
Martin von BergenDepartment of Proteomics, Helmholtz Centre for Environmental Research-UFZ, Permoserstr. 15, Leipzig, 04318, Germany ; Department of Metabolomics, Helmholtz Centre for Environmental Research-UFZ, Permoserstr. 15, Leipzig, 04318, Germany ; Department of Biotechnology, Chemistry and Environmental Engineering, University of Aalborg, Sohngaardsholmsvej 49, Aalborg, 9000, Denmark.
Susann MüllerDepartment of Environmental Microbiology, Helmholtz Centre for Environmental Research-UFZ, Permoserstr. 15, Leipzig, 04318, Germany.
Ralf TakorsInstitute for Biochemical Engineering, University of Stuttgart, Allmandring 31, Stuttgart, Germany.
Helmholtz Centre for Environmental Research · DEUniversity of Stuttgart · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population heterogeneity occurring in industrial microbial bioprocesses is regarded as a putative effector causing performance loss in large scale. While the existence of subpopulations is a commonly accepted fact, their appearance and impact on process performance still remains rather unclear. During cell cycling, distinct subpopulations differing in cell division state and DNA content appear which contribute individually to the efficiency of the bioprocess. To identify stressed or impaired subpopulations, we analyzed the interplay of growth rate, cell cycle and phenotypic profile of subpopulations by using flow cytometry and cell sorting in conjunction with mass spectrometry based global proteomics. Adjusting distinct growth rates in chemostats with the model strain Pseudomonas putida KT2440, cells were differentiated by DNA content reflecting different cell cycle stages. The proteome of separated subpopulations at given growth rates was found to be highly similar, while different growth rates caused major changes of the protein inventory with respect to e.g. carbon storage, motility, lipid metabolism and the translational machinery. In conclusion, cells in various cell cycle stages at the same growth rate were found to have similar to identical proteome profiles showing no significant population heterogeneity on the proteome level. In contrast, the growth rate clearly determines the protein composition and therefore the metabolic strategy of the cells.

Indexed as

Cell cycleFlow cytometryHeterogeneityProteomePseudomonas putidaSubpopulations

Identifiers

PMID25401072
PMCPMC4230896
OpenAlexW2123545527

What OpenQuestion holds

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LicenceCC BY
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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.