Evidence map›Paper›PMID 27092112›Full record

ArticleFrontiers in microbiology2016

Proteogenomic Analysis of Mycobacterium smegmatis Using High Resolution Mass Spectrometry.

Matthys G Potgieter, Kehilwe C Nakedi, Jon M Ambler, Andrew J M Nel, Shaun Garnett, Nelson C Soares, Nicola Mulder, Jonathan M Blackburn

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Integrated Multi-Omic Analysis ofFrontiers in microbiology · 2018
    Article
  9. Proteogenomic Analysis and Discovery of Immune Antigens inMolecular & cellular proteomics : MCP · 2017
    Article
  10. Methods, Tools and Current Perspectives in Proteogenomics.Molecular & cellular proteomics : MCP · 2017
    Review
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.

Matthys G PotgieterComputational Biology Division, Department of Integrative Biomedical Sciences, IDM, University of Cape Town Cape Town, South Africa.
Kehilwe C NakediDivision of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, IDM, University of Cape Town Cape Town, South Africa.
Jon M AmblerComputational Biology Division, Department of Integrative Biomedical Sciences, IDM, University of Cape Town Cape Town, South Africa.
Andrew J M NelDivision of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, IDM, University of Cape Town Cape Town, South Africa.
Shaun GarnettDivision of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, IDM, University of Cape Town Cape Town, South Africa.
Nelson C SoaresDivision of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, IDM, University of Cape Town Cape Town, South Africa.
Nicola MulderComputational Biology Division, Department of Integrative Biomedical Sciences, IDM, University of Cape Town Cape Town, South Africa.
Jonathan M BlackburnDivision of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, IDM, University of Cape Town Cape Town, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biochemical evidence is vital for accurate genome annotation. The integration of experimental data collected at the proteome level using high resolution mass spectrometry allows for improvements in genome annotation by providing evidence for novel gene models, while validating or modifying others. Here, we report the results of a proteogenomic analysis of a reference strain of Mycobacterium smegmatis (mc(2)155), a fast growing model organism for the pathogenic Mycobacterium tuberculosis-the causative agent for Tuberculosis. By integrating high throughput LC/MS/MS proteomic data with genomic six frame translation and ab initio gene prediction databases, a total of 2887 ORFs were identified, including 2810 ORFs annotated to a Reference protein, and 63 ORFs not previously annotated to a Reference protein. Further, the translational start site (TSS) was validated for 558 Reference proteome gene models, while upstream translational evidence was identified for 81. In addition, N-terminus derived peptide identifications allowed for downstream TSS modification of a further 24 gene models. We validated the existence of six previously described interrupted coding sequences at the peptide level, and provide evidence for four novel frameshift positions. Analysis of peptide posterior error probability (PEP) scores indicates high-confidence novel peptide identifications and shows that the genome of M. smegmatis mc(2)155 is not yet fully annotated. Data are available via ProteomeXchange with identifier PXD003500.

Indexed as

genome annotationmass spectrometryMycobacterium smegmatis mc2155proteogenomicsproteomics

Identifiers

PMID27092112
PMCPMC4821088

What OpenQuestion holds

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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.