Evidence map›Paper›PMID 22408620›Full record

ArticleFrontiers in pharmacology2012

Sirtuins as regulators of the yeast metabolic network.

Markus Ralser, Steve Michel, Michael Breitenbach

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2012. 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
1.8field-weighted citation impact, top 15% 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

9 citing papers in PubMed, 21 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 2 institutions in 3 countries.

Markus RalserDepartment of Biochemistry, Cambridge Systems Biology Centre, University of Cambridge Cambridge, UK.
Steve Michel
Michael Breitenbach
Max Planck Society · DEUniversity of Salzburg · AT

Funding

European Research Council 260809
6 · The paper itself

Abstract

There is growing evidence that the metabolic network is an integral regulator of cellular physiology. Dynamic changes in metabolite concentrations, metabolic flux, or network topology act as reporters of biological or environmental signals, and are required for the cell to trigger an appropriate biological reaction. Changes in the metabolic network are recognized by specific sensory macromolecules and translated into a transcriptional or translational response. The protein family of sirtuins, discovered more than 30 years ago as regulators of silent chromatin, seems to fulfill the role of a metabolic sensor during aging and conditions of caloric restriction. The archetypal sirtuin, yeast silentinformationregulator2 (SIR2), is an NAD(+) dependent protein deacetylase that interacts with metabolic enzymes glyceraldehyde-3-phosphate dehydrogenase and alcohol dehydrogenase, as well as enzymes involved in NAD(H) synthesis, that provide or deprive NAD(+) in its close proximity. This influences sirtuin activity, and facilitates a dynamic response of the metabolic network to changes in metabolism with effects on physiology and aging. The molecular network downstream Sir2, however, is complex. In just two orders, Sir2's metabolism related interactions span half of the yeast proteome, and are connected with virtually every physiological process. Thus, although it is fundamental to analyze single molecular mechanisms, it is at the same time crucial to consider this genome-scale complexity when correlating single molecular events with complex phenotypes such as aging, cell growth, or stress resistance.

Indexed as

agingcaloric restrictionglycolysismetabolic networknicotinamidepentose phosphate pathwayredox statesirtuins

Identifiers

PMID22408620
PMCPMC3296958
OpenAlexW2042901701

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.