Evidence map›Paper›PMID 32723790›Full record

ArticlemSystems2020

Selective Translation of Low Abundance and Upregulated Transcripts in Halobacterium salinarum.

Adrián López García de Lomana, Ulrike Kusebauch, Arjun V Raman, Min Pan, Serdar Turkarslan, Alan P R Lorenzetti, Robert L Moritz, Nitin S Baliga

Open access · goldAbstract read
In one paragraph

Article in mSystems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

7 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Molecular acclimation ofFrontiers in microbiology · 2022
    Article
  6. Genes · 2021
    Article
  7. 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

8 authors at 3 institutions in 2 countries.

Adrián López García de Lomana *Institute for Systems Biology, Seattle, Washington, USA.
Ulrike Kusebauch *Institute for Systems Biology, Seattle, Washington, USA.
Arjun V Raman *Institute for Systems Biology, Seattle, Washington, USA.
Min PanInstitute for Systems Biology, Seattle, Washington, USA.
Serdar TurkarslanInstitute for Systems Biology, Seattle, Washington, USA.
Alan P R LorenzettiInstitute for Systems Biology, Seattle, Washington, USA.
Robert L MoritzInstitute for Systems Biology, Seattle, Washington, USA.
Nitin S BaligaInstitute for Systems Biology, Seattle, Washington, USA nbaliga@systemsbiology.org.
Institute for Systems Biology · USUniversidade de São Paulo · BRUniversity of Washington · US

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DUDLEY, AIMEE M · 2006 to 2016
$30.6M
A systems analysis of drug tolerance in Mycobacterium tuberculosisR01AI128215 · NIAID · INSTITUTE FOR SYSTEMS BIOLOGY · PI Nitin S Baliga · 2017 to 2026
$8.8M
Shortening the development cycle time of Trans Proteomic Pipeline tools with high performance computingR01GM087221 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC, MORITZ, ROBERT L · 2010 to 2021
$6.0M
Site Specific Immunophenotyping Assays of COVID19 Patients to Align with NIAID National StudyR01AI141953 · NIAID · INSTITUTE FOR SYSTEMS BIOLOGY · PI BALIGA, NITIN S · 2019 to 2023
$5.7M
NIAID NIH HHS R01 AI128215NIAID NIH HHS R01 AI141953NIGMS NIH HHS P50 GM076547NIGMS NIH HHS R01 GM087221
6 · The paper itself

Abstract

When organisms encounter an unfavorable environment, they transition to a physiologically distinct, quiescent state wherein abundant transcripts from the previous active growth state continue to persist, albeit their active transcription is downregulated. In order to generate proteins for the new quiescent physiological state, we hypothesized that the translation machinery must selectively translate upregulated transcripts in an intracellular milieu crowded with considerably higher abundance transcripts from the previous active growth state. Here, we have analyzed genome-wide changes in the transcriptome (RNA sequencing [RNA-seq]), changes in translational regulation and efficiency by ribosome profiling across all transcripts (ribosome profiling [Ribo-seq]), and protein level changes in assembled ribosomal proteins (sequential window acquisition of all theoretical mass spectra [SWATH-MS]) to investigate the interplay of transcriptional and translational regulation in

Indexed as

archaeaproteomicsribosome heterogeneityribosome profilingselective translationtranscription-translation interplaytranscriptomicstranslational regulation

Identifiers

PMID32723790
PMCPMC7394353
OpenAlexW3046120175

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.