Evidence map›Paper›PMID 33369128›Full record

ArticleMicrobial biotechnology2021

Transcriptional profiling of the stringent response mutant strain E. coli SR reveals enhanced robustness to large-scale conditions.

Martin Ziegler, Julia Zieringer, Ralf Takors

Open access · goldAbstract read
In one paragraph

Article in Microbial biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 24% 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

3 citing papers in PubMed, 11 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

3 authors at 1 institution in 1 country.

Martin ZieglerInstitute of Biochemical Engineering, University of Stuttgart, Stuttgart, Germany.ORCID 0000-0003-2137-5234
Julia ZieringerInstitute of Biochemical Engineering, University of Stuttgart, Stuttgart, Germany.
Ralf TakorsInstitute of Biochemical Engineering, University of Stuttgart, Stuttgart, Germany.
University of Stuttgart · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In large-scale fed-batch production processes, microbes are exposed to heterogeneous substrate availability caused by long mixing times. Escherichia coli, the most common industrial host for recombinant protein production, reacts by recurring accumulation of the alarmone ppGpp and energetically wasteful transcriptional strategies. Here, we compare the regulatory responses of the stringent response mutant strain E. coli SR and its parent strain E. coli MG1655 to repeated nutrient starvation in a two-compartment scale-down reactor. Our data show that E. coli SR can withstand these stress conditions without a ppGpp-mediated stress response maintaining fully functional ammonium uptake and biomass formation. Furthermore, E. coli SR exhibited a substantially reduced short-term transcriptional response compared to E. coli MG1655 (less than half as many differentially expressed genes). E. coli SR proceeded adaptation via more general SOS response pathways by initiating negative regulation of transcription, translation and cell division. Our results show that locally induced stress responses propagating through the bioreactor do not result in cyclical induction and repression of genes in E. coli SR, but in a reduced and coordinated response, which makes it potentially suitable for large-scale production processes.

Indexed as

Escherichia coliEscherichia coli ProteinsAdaptation, PhysiologicalGene Expression Regulation, BacterialGuanosine TetraphosphateEscherichia coli ProteinsGuanosine Tetraphosphate

Identifiers

PMID33369128
PMCPMC8085953
OpenAlexW3117372104

What OpenQuestion holds

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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 OpenQuestion graph.