Evidence map›Paper›PMID 24799698›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2014

Bet-hedging during bacterial diauxic shift.

Ana Solopova, Jordi van Gestel, Franz J Weissing, Herwig Bachmann, Bas Teusink, Jan Kok, Oscar P Kuipers

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 130 papers.

0numbers the graph read from it
0cells of the map it votes in
130citing papers in PubMed
–field-weighted citation impact
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

130 citing papers in PubMed.

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70 more citing papers are in PubMed but not listed here.

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.

Ana SolopovaDepartment of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, and.
Jordi van GestelTheoretical Biology Group, Centre for Ecological and Evolutionary Studies, University of Groningen, 9747 AG, Groningen, The Netherlands;
Franz J WeissingTheoretical Biology Group, Centre for Ecological and Evolutionary Studies, University of Groningen, 9747 AG, Groningen, The Netherlands;Systems Biology Centre Groningen, University of Groningen, 9713 AV, Groningen, The Netherlands;
Herwig BachmannFaculty of Earth and Life Sciences, Systems Bioinformatics, Centre for Integrative Bioinformatics Vrije Universiteit/Netherlands Institute for Systems Biology, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands;Top Institute Food and Nutrition, 6700 AN, Wageningen, The Netherlands; and.
Bas TeusinkFaculty of Earth and Life Sciences, Systems Bioinformatics, Centre for Integrative Bioinformatics Vrije Universiteit/Netherlands Institute for Systems Biology, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands;Kluyver Centre for Genomics of Industrial Fermentation, 2628 BC, Delft, The Netherlands.
Jan KokDepartment of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, andTop Institute Food and Nutrition, 6700 AN, Wageningen, The Netherlands; and.
Oscar P KuipersDepartment of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, andTop Institute Food and Nutrition, 6700 AN, Wageningen, The Netherlands; andKluyver Centre for Genomics of Industrial Fermentation, 2628 BC, Delft, The Netherlands o.p.kuipers@rug.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When bacteria grow in a medium with two sugars, they first use the preferred sugar and only then start metabolizing the second one. After the first exponential growth phase, a short lag phase of nongrowth is observed, a period called the diauxie lag phase. It is commonly seen as a phase in which the bacteria prepare themselves to use the second sugar. Here we reveal that, in contrast to the established concept of metabolic adaptation in the lag phase, two stable cell types with alternative metabolic strategies emerge and coexist in a culture of the bacterium Lactococcus lactis. Only one of them continues to grow. The fraction of each metabolic phenotype depends on the level of catabolite repression and the metabolic state-dependent induction of stringent response, as well as on epigenetic cues. Furthermore, we show that the production of alternative metabolic phenotypes potentially entails a bet-hedging strategy. This study sheds new light on phenotypic heterogeneity during various lag phases occurring in microbiology and biotechnology and adjusts the generally accepted explanation of enzymatic adaptation proposed by Monod and shared by scientists for more than half a century.

Indexed as

Bacterial Physiological PhenomenaAdaptation, PhysiologicalCarbohydratesCell Culture TechniquesCellobioseEpigenesis, GeneticGlucoseLactococcus lactisPhenotypeTime FactorsCarbohydratesCellobioseGlucoseGram-positive bacteriametabolic fitnessphenotypic heterogeneity

Identifiers

PMID24799698
PMCPMC4034238

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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.