Evidence map›Paper›PMID 19436767›Full record

ArticleJournal of proteomics & bioinformatics2009

Principal Component Analysis of Proteome Dynamics in Iron-starved Mycobacterium Tuberculosis.

Prahlad K Rao, Qingbo Li

Abstract read
In one paragraph

Article in Journal of proteomics & bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
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

17 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. EuPA open proteomics · 2016
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Tuberculosis: global approaches to a global disease.Current opinion in biotechnology · 2010
    Review
  15. Article
  16. Article
  17. A systems biology approach to study the phagosomal proteome modulated by mycobacterial infections.International journal of clinical and experimental medicine · 2009
    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.

Prahlad K RaoCenter for Pharmaceutical Biotechnology, College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois 60607, USA.
Qingbo Li

Funding

Intracellular mycobacterial proteomeR03AI073469 · NIAID · UNIVERSITY OF ILLINOIS AT CHICAGO · PI LI, QINGBO · 2008 to 2008
$79k
NIAID NIH HHS R03 AI073469
6 · The paper itself

Abstract

The goal of this study is to use principal component analysis (PCA) for multivariate analysis of proteome dynamics based on both protein abundance and turnover information generated by high-resolution mass spectrometry. We previously reported assessing protein dynamics in iron-starved Mycobacterium tuberculosis, revealing interesting interconnection among the cellular processes involving protein synthesis, degradation, and secretion (Anal. Chem. 80, 6860-9). In this study, we use target-decoy database search approach to select peptides for quantitation at a false discovery rate of 4.2%. We further use PCA to reduce the data dimensions for simpler interpretation. The PCA results indicate that the protein turnover and relative abundance properties are approximately orthogonal in the data space defined by the first three principal components. We show the potential of the Hotelling's T2 (T2) value as a quantifiable index for comparing changes between protein functional categories. The T2 value represents the gross change of a protein in both abundance and turnover. Close examination of the antigen 85 complex demonstrates that T2 correctly predicts the coordinated changes of the antigen 85 complex proteins. The multi-dimensional protein dynamics data further reveal the secretion of the antigen 85 complex. Overall, this study demonstrates PCA as an effective means to facilitate interpretation of the multivariate proteome dynamics dataset which otherwise would remain a significant challenge using traditional methods.

Identifiers

PMID19436767
PMCPMC2680294

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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.