Evidence map›Paper›PMID 26725116›Full record

ArticleCell reports2016

The Cost of Protein Production.

Moshe Kafri, Eyal Metzl-Raz, Ghil Jona, Naama Barkai

Open access · goldAbstract read
In one paragraph

Article in Cell reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 199 papers.

0numbers the graph read from it
0cells of the map it votes in
199citing papers in PubMed
13.3field-weighted citation impact, top 1% 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

199 citing papers in PubMed, 398 citations in OpenAlex.

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  16. Visualizing C. difficile During Murine Infection.Methods in molecular biology (Clifton, N.J.) · 2026
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139 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

4 authors at 1 institution in 1 country.

Moshe KafriDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel.
Eyal Metzl-RazDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel.
Ghil JonaDepartment of Biological Services, Weizmann Institute of Science, Rehovot 76100, Israel.
Naama BarkaiDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel. Electronic address: naama.barkai@weizmann.ac.il.
Weizmann Institute of Science · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The economy of protein production is central to cell physiology, being intimately linked with cell division rate and cell size. Attempts to model cellular physiology are limited by the scarcity of experimental data defining the molecular processes limiting protein expression. Here, we distinguish the relative contribution of gene transcription and protein translation to the slower proliferation of budding yeast producing excess levels of unneeded proteins. In contrast to widely held assumptions, rapidly growing cells are not universally limited by ribosome content. Rather, transcription dominates cost under some conditions (e.g., low phosphate), translation in others (e.g., low nitrogen), and both in other conditions (e.g., rich media). Furthermore, cells adapted to enforced protein production by becoming larger and increasing their endogenous protein levels, suggesting limited competition for common resources. We propose that rapidly growing cells do not exhaust their resources to maximize growth but maintain sufficient reserves to accommodate changing requirements.

Indexed as

Gene Expression Regulation, FungalProtein BiosynthesisSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsTranscription, GeneticSaccharomyces cerevisiae Proteinsbudding yeastfitness costprotein burdenprotein synthesis

Identifiers

PMID26725116
PMCPMC4709330
OpenAlexW2219121760

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.