Evidence map›Paper›PMID 34343023›Full record

ArticleAnnual review of microbiology2021

Quantitative Control for Stoichiometric Protein Synthesis.

James C Taggart, Jean-Benoît Lalanne, Gene-Wei Li

Open access · bronzeAbstract read
In one paragraph

Article in Annual review of microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

13 citing papers in PubMed, 18 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.

James C TaggartDepartment of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA; email: jtaggart@mit.edu, gwli@mit.edu.
Jean-Benoît LalanneDepartment of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA; email: jtaggart@mit.edu, gwli@mit.edu.
Gene-Wei LiDepartment of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA; email: jtaggart@mit.edu, gwli@mit.edu.
Massachusetts Institute of Technology · US

Funding

PRE-DOCTORAL TRAINING IN THE BIOLOGICAL SCIENCEST32GM007287 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BELL, STEPHEN P., KEATING, AMY E · 1985 to 2019
$40.8M
Evolution and Regulation of Bacterial Proteome CompositionR35GM124732 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Gene-Wei Li · 2017 to 2026
$3.8M
Howard Hughes Medical InstituteNIGMS NIH HHS R35 GM124732NIGMS NIH HHS T32 GM007287
6 · The paper itself

Abstract

Bacterial protein synthesis rates have evolved to maintain preferred stoichiometries at striking precision, from the components of protein complexes to constituents of entire pathways. Setting relative protein production rates to be well within a factor of two requires concerted tuning of transcription, RNA turnover, and translation, allowing many potential regulatory strategies to achieve the preferred output. The last decade has seen a greatly expanded capacity for precise interrogation of each step of the central dogma genome-wide. Here, we summarize how these technologies have shaped the current understanding of diverse bacterial regulatory architectures underpinning stoichiometric protein synthesis. We focus on the emerging expanded view of bacterial operons, which encode diverse primary and secondary mRNA structures for tuning protein stoichiometry. Emphasis is placed on how quantitative tuning is achieved. We discuss the challenges and open questions in the application of quantitative, genome-wide methodologies to the problem of precise protein production.

Indexed as

Escherichia coliOperonProtein BiosynthesisProteinsRNA, MessengerTranscription, GeneticProteinsRNA, Messengerdifferential RNA stabilitydifferential translationexpression stoichiometryoperon mRNA isoformproportional synthesis

Identifiers

PMID34343023
PMCPMC8720029
OpenAlexW3189126572

What OpenQuestion holds

Textmetadata
LicenceTDM
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.