Evidence map›Paper›PMID 19783922›Full record

ReviewMolecules (Basel, Switzerland)2009

Protein turnover in mycobacterial proteomics.

Prahlad K Rao, Qingbo Li

Open access · goldAbstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2009. 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
1.6field-weighted citation impact, top 19% 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, 17 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Tuberculosis: global approaches to a global disease.Current opinion in biotechnology · 2010
    Review
  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

2 authors at 1 institution in 1 country.

Prahlad K RaoCenter for Pharmaceutical Biotechnology, College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois 60607, USA. rkrish4@uic.edu
Qingbo Li
University of Illinois Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the biology of Mycobacterium tuberculosis is one of the primary challenges in current tuberculosis research. Investigation of mycobacterial biology using the systems biology approach has deciphered much information with regard to the bacilli and tuberculosis pathogenesis. The modulation of its environment and the ability to enter a dormant phase are the hallmarks of M. tuberculosis. Until now, proteome studies have been able to understand much about the role of various proteins, mostly in growing M. tuberculosis cells. It has been difficult to study dormant M. tuberculosis by conventional proteomic techniques with very few proteins being found to be differentially expressed. Discrepancy between proteome and transcriptome studies lead to the conclusion that a certain aspect of the mycobacterial proteome is not being explored. Analysis of protein turnover may be the answer to this dilemma. This review, while giving a gist of the proteome response of mycobacteria to various stresses, analyzes the data obtained from abundance studies versus data from protein turnover studies in M. tuberculosis. This review brings forth the point that protein turnover analysis is capable of discerning more subtle changes in protein synthesis, degradation, and secretion activities. Thus, turnover studies could be incorporated to provide a more in-depth view into the proteome, especially in dormant or persistent cells. Turnover analysis might prove helpful in drug discovery and a better understanding of the dynamic nature of the proteome of mycobacteria.

Indexed as

ProteomicsBacterial ProteinsMycobacteriumProteomeBacterial ProteinsProteome

Identifiers

PMID19783922
PMCPMC6254974
OpenAlexW2048419230

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.