Evidence map›Paper›PMID 39714213›Full record

ArticlemSystems2025

Revealing systematic changes in the transcriptome during the transition from exponential growth to stationary phase.

Hyun Gyu Lim, Ye Gao, Kevin Rychel, Cameron Lamoureux, Xuwen A Lou, Bernhard O Palsson

Abstract read
In one paragraph

Article in mSystems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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.

Hyun Gyu LimDepartment of Biological Sciences and Bioengineering, Inha University, Incheon, South Korea.ORCID 0000-0002-0469-2388
Ye GaoDepartment of Bioengineering, University of California, San Diego, California, USA.
Kevin RychelDepartment of Bioengineering, University of California, San Diego, California, USA.
Cameron LamoureuxDepartment of Bioengineering, University of California, San Diego, California, USA.
Xuwen A LouDepartment of Bioengineering, University of California, San Diego, California, USA.
Bernhard O PalssonDepartment of Bioengineering, University of California, San Diego, California, USA.ORCID 0000-0003-2357-6785

Funding

National Research Foundation of Korea (NRF) RS-2024-00334792National Research Foundation of Korea (NRF) RS-2024-00399277U.S. Department of Energy (DOE) DE-AC02-05CH11231
6 · The paper itself

Abstract

The composition of bacterial transcriptomes is determined by the transcriptional regulatory network (TRN). The TRN regulates the transition from one physiological state to another. Here, we use independent component analysis to monitor the composition of the transcriptome during the transition from the exponential growth phase to the stationary phase. With IMPORTANCE: Nutrient limitations are critical environmental perturbations in bacterial physiology. Despite its importance, a detailed understanding of how bacterial transcriptomes are adjusted has been limited. By utilizing independent component analysis (ICA) to decompose transcriptome data, this study reveals key regulatory events that enable bacteria to adapt to nutrient limitations. The findings not only highlight common responses, such as the stringent response, but also condition-specific regulatory shifts associated with carbon, nitrogen, and sulfur starvation. The insights gained from this work advance our knowledge of bacterial physiology, gene regulation, and metabolic adaptation.

Indexed as

Escherichia coli K12TranscriptomeCarbonGene Expression Regulation, BacterialGene Regulatory NetworksNitrogenSulfurCarbonNitrogenSulfurindependent component analysisnutrient starvationRNA-sequencingstationary phasestresssystems biologytranscriptome

Identifiers

PMID39714213
PMCPMC11748552

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LicenceCC BY
Read underepoch 390

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.