Evidence map›Paper›PMID 38417437›Full record

ArticleCell systems2024

Cross-evaluation of E. coli's operon structures via a whole-cell model suggests alternative cellular benefits for low- versus high-expressing operons.

Gwanggyu Sun, Mialy M DeFelice, Taryn E Gillies, Travis A Ahn-Horst, Cecelia J Andrews, Markus Krummenacker, Peter D Karp, Jerry H Morrison, Markus W Covert

Open access · greenAbstract read
In one paragraph

Article in Cell systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
4.4field-weighted citation impact, top 6% 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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
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

9 authors at 2 institutions in 1 country.

Gwanggyu SunDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Mialy M DeFeliceDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Taryn E GilliesDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Travis A Ahn-HorstDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Cecelia J AndrewsDepartment of Developmental Biology, Stanford University, Stanford, CA 94305, USA.
Markus KrummenackerSRI International, Menlo Park, CA 94025, USA.
Peter D KarpSRI International, Menlo Park, CA 94025, USA.
Jerry H MorrisonDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Markus W CovertDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA. Electronic address: mcovert@stanford.edu.
Stanford University · USSRI International · US

Funding

Multi-scale, model-driven exploration of sub-generational gene expression in bacteria: individual consequences, population benefitsR01GM140008 · NIGMS · STANFORD UNIVERSITY · PI COVERT, MARKUS W · 2021 to 2024
$2.2M
Deep Curation via an Integrated Whole-Cell Computational ModelR01LM013229 · NLM · STANFORD UNIVERSITY · PI COVERT, MARKUS W · 2020 to 2023
$1.5M
A model-driven investigation into the role of operon structure and sub-generational expression in Escherichia coliF32GM137528 · NIGMS · STANFORD UNIVERSITY · PI GILLIES, TARYN · 2020 to 2020
$54k
NIGMS NIH HHS F32 GM137528NIGMS NIH HHS R01 GM140008NLM NIH HHS R01 LM013229
6 · The paper itself

Abstract

Many bacteria use operons to coregulate genes, but it remains unclear how operons benefit bacteria. We integrated E. coli's 788 polycistronic operons and 1,231 transcription units into an existing whole-cell model and found inconsistencies between the proposed operon structures and the RNA-seq read counts that the model was parameterized from. We resolved these inconsistencies through iterative, model-guided corrections to both datasets, including the correction of RNA-seq counts of short genes that were misreported as zero by existing alignment algorithms. The resulting model suggested two main modes by which operons benefit bacteria. For 86% of low-expression operons, adding operons increased the co-expression probabilities of their constituent proteins, whereas for 92% of high-expression operons, adding operons resulted in more stable expression ratios between the proteins. These simulations underscored the need for further experimental work on how operons reduce noise and synchronize both the expression timing and the quantity of constituent genes. A record of this paper's transparent peer review process is included in the supplemental information.

Indexed as

Escherichia coliOperonBacteriacellular heterogeneitydeep curationmechanistic modelingmicrobiologymodel-driven discoveryoperonRNA sequencingtranscriptional regulationtranscription unit structurewhole-cell modeling

Identifiers

PMID38417437
PMCPMC10957310
OpenAlexW4392203312

What OpenQuestion holds

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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.