Evidence map›Paper›PMID 20470417›Full record

ArticleBMC systems biology2010

Large scale physiological readjustment during growth enables rapid, comprehensive and inexpensive systems analysis.

Marc T Facciotti, Wyming L Pang, Fang-yin Lo, Kenia Whitehead, Tie Koide, Ken-ichi Masumura, Min Pan, Amardeep Kaur, David J Larsen, David J Reiss and 6 more

Open access · diamondAbstract read
In one paragraph

Article in BMC systems biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

14 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. TheScientificWorldJournal · 2022
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  12. Hot transcriptomics.Archaea (Vancouver, B.C.) · 2011
    Article
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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

16 authors at 5 institutions in 2 countries.

Marc T FacciottiInstitute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. mtfacciotti@ucdavis.edu
Wyming L Pang
Fang-yin Lo
Kenia Whitehead
Tie Koide
Ken-ichi Masumura
Min Pan
Amardeep Kaur
David J Larsen
David J Reiss
Linh Hoang
Ewa Kalisiak
Trent Northen
Sunia A Trauger
Gary Siuzdak
Nitin S Baliga
Institute for Systems Biology · USScripps Research Institute · USSeattle University · USNational Institute of Health Sciences · JPUniversity of California, Davis · US

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI BALIGA, NITIN S · 2006 to 2016
$30.6M
Interrogation of systems level mechanisms controlling DNA repair processesR01GM077398 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI BALIGA, NITIN S · 2007 to 2010
$1.3M
NIGMS NIH HHS 1R01GM077398-01A2NIGMS NIH HHS P50 GM076547NIGMS NIH HHS P50GM076547
6 · The paper itself

Abstract

backgroundRapidly characterizing the operational interrelationships among all genes in a given organism is a critical bottleneck to significantly advancing our understanding of thousands of newly sequenced microbial and eukaryotic species. While evolving technologies for global profiling of transcripts, proteins, and metabolites are making it possible to comprehensively survey cellular physiology in newly sequenced organisms, these experimental techniques have not kept pace with sequencing efforts. Compounding these technological challenges is the fact that individual experiments typically only stimulate relatively small-scale cellular responses, thus requiring numerous expensive experiments to survey the operational relationships among nearly all genetic elements. Therefore, a relatively quick and inexpensive strategy for observing changes in large fractions of the genetic elements is highly desirable.

resultsWe have discovered in the model organism Halobacterium salinarum NRC-1 that batch culturing in complex medium stimulates meaningful changes in the expression of approximately two thirds of all genes. While the majority of these changes occur during transition from rapid exponential growth to the stationary phase, several transient physiological states were detected beyond what has been previously observed. In sum, integrated analysis of transcript and metabolite changes has helped uncover growth phase-associated physiologies, operational interrelationships among two thirds of all genes, specialized functions for gene family members, waves of transcription factor activities, and growth phase associated cell morphology control.

conclusionsSimple laboratory culturing in complex medium can be enormously informative regarding the activities of and interrelationships among a large fraction of all genes in an organism. This also yields important baseline physiological context for designing specific perturbation experiments at different phases of growth. The integration of such growth and perturbation studies with measurements of associated environmental factor changes is a practical and economical route for the elucidation of comprehensive systems-level models of biological systems.

Indexed as

Systems AnalysisSystems BiologyChromatography, LiquidEscherichia coliGene Expression ProfilingGene Regulatory NetworksHalobacterium salinarumMass SpectrometryModels, BiologicalModels, GeneticOligonucleotide Array Sequence AnalysisPhenotypeRNA, MessengerTranscription, GeneticRNA, Messenger

Identifiers

PMID20470417
PMCPMC2880973
OpenAlexW2109406280

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.